naslovnica 54-1_naslovnica 49-1.qxd 17.2.2015 9:15 Page 1 4 ACTA GEOGRAPHICA SLOVENICA 10 GEOGRAFSKI ZBORNIK 2 • 54-1 • 2014 ACTA GEOGRAPHICA -145 Contents – Vsebina • Wolfgang TINTOR, Maja ANDRI^ IK Lateglacial studies in the western valleys of the Italian Julian Alps and in the Koritnica valley 7 NR SLOVENICA GEOGRAFSKI ZBORNIK Mateja BREG VALJAVEC O Detection of former landfills in gravel plain using geomorphometric analysis and High-Resolution LiDAR DTM 21 B Odkrivanje prikritih odlagali{~ odpadkov v prodni ravnini z geomorfometri~no analizo in LiDAR DMR 34 I Z Smiljana \UKI^IN, Jasmina \OR\EVI], Jelena MILANKOVI] K Spatial and social changes caused by the continuous exploitation of lignite in the Kolubara lignite basin, Serbia 41 SF Tamara LUKI], Milka BUBALO - @IVKOVI], Bojan \ER^AN, Gordana JOVANOVI] A Population Growth in the Border Villages of Srem, Serbia 51 R Lilijana [PRAH, Tatjana NOVAK, Jerneja FRIDL G The wellbeing of Slovenia's population by region: comparison of indicators with an emphasis on health 67 O Blaginja prebivalcev Slovenije po regijah: primerjava kazalnikov s poudarkom na zdravju 80 EG Ivana CRLJENKO • Some older sources for Croatian exonym analysis 89 A Daniel TUDORA, Mihail EVA IC A geographical methodology for assessing nodality of a road network. Case study on the western Moldavia 101 N Josef NAVRÁTIL, Miha LESJAK, Kamil PÍCHA, Stanislav MARTINÁT, Jana NAVRÁTILOVÁ, E Vivian L. WHITE BARAVALLE GILLIAM, Jaroslav KNOTEK, Tomá{ KU^ERA, Roman [VEC, V Zuzana BALOUNOVÁ, Josef RAJCHARD O The importance of vulnerable areas with potential tourism development: L a case study of the Bohemian forest and South Bohemia tourism regions 115 SA Vera GLIGORIJEVI], Mirjana DEVED@I], Ivan RATKAJ Localization factors and development strategies for producer services: a case study of Belgrade, Serbia 131 ICHP Spe cial issue – Natu ral hazards 2014 A Slobodan B. MARKOVI], Albert RUMAN, Milivoj B. GAVRILOV, R Thomas STEVENS, Matija ZORN, Blà KOMAC, Drago PERKO G Modelling of the Aral and Caspian seas drying out influence to climate and environmental changes 143 OE Jelena KOVA^EVI] - MAJKI], Marko V. MILO[EVI], Milena PANI], Dragana MILJANOVI], Jelena ]ALI] G Risk education in Serbia 163 AT Zorica SVIR^EV, Svetislav KRSTI], Tamara VA@I] C The phylosophy and applicability of ecoremediations for the protection of water ecosystems 179 A Radislav TO[I], Slavoljub DRAGI]EVI], Matija ZORN, Novica LOVRI] Landslide susceptibility zonation: A case study of the Municipality of Banja Luka (Bosnia and Herzegovina) 189 ISSN 1581-6613 9 1 8 5 1 7 7 0 1 0 1 6 6 2014 54 1 ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKI ZBORNIK 54-1 2014 2 ZNANSTVENORAZISKOVALNI CENTER SLOVENSKE AKADEMIJE ZNANOSTI IN UMETNOSTI GEOGRAFSKI IN[TITUT ANTONA MELIKA • RESEARCH CENTRE OF THE SLOVENIAN ACADEMY OF SCIENCES AND ARTS ANTON MELIK GEOGRAPHICAL INSTITUTE ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKI ZBORNIK 54-1 2014 LJUBLJANA 2014 ACTA GEOGRAPHICA SLOVENICA/GEOGRAFSKI ZBORNIK 54-1 2014 ISSN: 1581-6613 COBISS: 124775936 UDC/UDK: 91 © Geografski in{titut Antona Melika ZRC SAZU 2014 International editorial board/mednarodni uredni{ki odbor: Michael Bründl (Switzerland), Rok Cigli~ (Slovenia), Matej Gabrovec (Slovenia), Ivan Gams (Slovenia), Peter Jordan (Austria), Drago Kladnik (Slovenia), Blà Komac (Slovenia), Andrej Kranjc (Slovenia), Dénes Lóczy (Hungary), Simon McCharty (United Kingdom), Slobodan Markovi} (Serbia), Milan Oroèn Adami~ (Slovenija), Drago Perko (Slovenia), Marjan Ravbar (Slovenia), Ale{ Smrekar (Slovenia), Annett Steinführer (Germany), Mimi Urbanc (Slovenia), Matija Zorn (Slovenia). Editor-in-Chief/glavni urednik: Blà Komac (blaz.komacazrc-sazu.si) Executive editor/odgovorni urednik: Drago Perko (dragoazrc-sazu.si) Chief editor for physical geography/glavni urednik za fizi~no geografijo: Matija Zorn (matija.zornazrc-sazu.si) Chief editor for human geography/glavna urednica za drùbeno geografijo: Mimi Urbanc (mimiazrc-sazu.si) Chief editor for regional geography/glavni urednik za regionalno geografijo: Drago Kladnik (drago.kladnikazrc-sazu.si) Chief editor for regional planning/glavni urednik za regionalno planiranje: Janez Nared Chief editor for geographic information systems/glavni urednik za geografske informacijske sisteme: Rok Cigli~ (rok.ciglicazrc-sazu.si) Chief editor for environmental protection/glavni urednik za varstvo okolja: Ale{ Smrekar Editorial assistant/uredni{ki pomo~nik: Matjà Ger{i~ (matjaz.gersicazrc-sazu.si) Published by/izdajatelj: Geografski in{titut Antona Melika ZRC SAZU Issued by/zalònik: Zalòba ZRC Co-issued by/sozalònik: Slovenska akademija znanosti in umetnosti Address/Naslov: Geografski in{titut Antona Melika ZRC SAZU, Gosposka ulica 13, SI – 1000 Ljubljana, Slovenija The papers are available on-line in English and Slovenian language/ prispevki so v angle{kem in slovenskem jeziku dostopni na medmrèju: http://ags.zrc-sazu.si (English internet version ISSN: 1581-8314/slovenska internetna razli~ica ISSN: 1581–8314) Ordering/naro~anje: Zalòba ZRC Novi trg 2, p. p. 306, SI – 1001 Ljubljana, Slovenija Phone/telefon: +386 (0)1 470 64 64 Fax/faks: +386 (0)1 425 77 94 E-mail/e-po{ta: zalozbaazrc-sazu.si An nual subs crip tion/let na naro~ ni na: 20 € for indi vi duals/za posa mez ni ke, 28 € for insti tu tions/za usta no ve. Sin gle issue/cena posa mez ne {te vil ke: 12,50 € for indi vi duals/za posa mez ni ke, 16 € for insti tu tions/za usta no ve. Cartography/kartografija: Geografski in{titut Antona Melika ZRC SAZU Translations/prevodi: DEKS d. o. o. DTP/prelom: SYNCOMP, d. o. o. Printed by/tiskarna: Collegium Graphicum d. o. o. Print run/naklada: 400 copies/izvodov The journal is subsidized by the Slovenian Research Agency/revija izhaja s podporo Javne agencije za raziskovalno dejavnost Republike Slovenije. The journal is indexed in also/ revija je vklju~ena tudi v: SCIE (Science citation index expanded, IF 2009: 0,714; IF 2010: 0,346; IF 2011: 1,333; IF 2012: 0,484; IF 2013: 0,750), CGP (Current geographical publications), Directory of Open Access Journals, EBSCOhost, Electronic publishing Center, Find in a library, GEOBASE Journals, GEODOK (Virtual Geographic Library Database), Geosource, JS (Journal Citation Reports/Science Edition), OHSU Electronic Journals, Google scholar, Geoscience e-Journals, FRANCIS. Front cover photography: Persistence – Pillar of the Daladier bridge (Avignon) in the Rhone river (photograph: Anej Viskovi}). Fotografija na naslovnici: Vztrajnost – nosilec mostu Daladier (Avignon) v reki Roni (fotografija: Anej Viskovi}). ACTA GEOGRAPHICA SLOVENICA – GEOGRAFSKI ZBORNIK ISSN: 1581-6613 UDC – UDK: 91 Number – {tevilka: 54-1 Year – leto: 2014 Contents – Vsebina Wolfgang TINTOR, Maja ANDRI^ Lateglacial studies in the western valleys of the Italian Julian Alps and in the Koritnica valley 7 Mateja BREG VALJAVEC Detection of former landfills in gravel plain using geomorphometric analysis and High-Resolution LiDAR DTM 21 Odkrivanje prikritih odlagali{~ odpadkov v prodni ravnini z geomorfometri~no analizo in LiDAR DMR 34 Smiljana \UKI^IN, Jasmina \OR\EVI], Jelena MILANKOVI] Spatial and social changes caused by the continuous exploitation of lignite in the Kolubara lignite basin, Serbia 41 Tamara LUKI], Milka BUBALO - @IVKOVI], Bojan \ER^AN, Gordana JOVANOVI] Population Growth in the Border Villages of Srem, Serbia 51 Lilijana [PRAH, Tatjana NOVAK, Jerneja FRIDL The wellbeing of Slovenia's population by region: comparison of indicators with an emphasis on health 67 Blaginja prebivalcev Slovenije po regijah: primerjava kazalnikov s poudarkom na zdravju 80 Ivana CRLJENKO Some older sources for Croatian exonym analysis 89 Daniel TUDORA, Mihail EVA A geographical methodology for assessing nodality of a road network. Case study on the western Moldavia 101 Josef NAVRÁTIL, Miha LESJAK, Kamil PÍCHA, Stanislav MARTINÁT, Jana NAVRÁTILOVÁ, Vivian L. WHITE BARAVALLE GILLIAM, Jaroslav KNOTEK, Tomá{ KU^ERA, Roman [VEC, Zuzana BALOUNOVÁ, Josef RAJCHARD The importance of vulnerable areas with potential tourism development: a case study of the Bohemian forest and South Bohemia tourism regions 115 5 Vera GLIGORIJEVI], Mirjana DEVED@I], Ivan RATKAJ Localization factors and development strategies for producer services: a case study of Belgrade, Serbia 131 Spe cial issue – Natu ral hazards 2014 Slobodan B. MARKOVI], Albert RUMAN, Milivoj B. GAVRILOV, Thomas STEVENS, Matija ZORN, Blà KOMAC, Drago PERKO Modelling of the Aral and Caspian seas drying out influence to climate and environmental changes 143 Jelena KOVA^EVI] - MAJKI], Marko V. MILO[EVI], Milena PANI], Dragana MILJANOVI], Jelena ]ALI] Risk education in Serbia 163 Zorica SVIR^EV, Svetislav KRSTI], Tamara VA@I] The phylosophy and applicability of ecoremediations for the protection of water ecosystems 179 Radislav TO[I], Slavoljub DRAGI]EVI], Matija ZORN, Novica LOVRI] Landslide susceptibility zonation: A case study of the Municipality of Banja Luka (Bosnia and Herzegovina) 189 6 Acta geographica Slovenica, 54-1, 2014, 7–20 LATEGLACIAL STUDIES IN THE WESTERN VALLEYS OF THE ITALIAN JULIAN ALPS AND IN THE KORITNICA VALLEY Wolfgang Tintor, Maja Andri~ ROTIN TGNAGFLOW Dogna valley with Montasio, Jof di Miez and Monte Zabus. Positon Chiout di Gus. Wolfgang Tintor, Maja Andri~, Lateglacial studies in the western valleys of the Italian Julian Alps and in the Koritnica valley Lateglacial studies in the western valleys of the Italian Julian Alps and in the Koritnica valley DOI: http://dx.doi.org/10.3986/AGS54101 UDC: 911.2:551.435.4(234.323.6) COBISS: 1.01 ABSTRACT: Different from the northern valleys of the Italian Julian Alps the bottoms of the western val- leys do not contain any late-pleistocene moraines. However, common to all valleys is the large glaciation most probably in the Gschnitz-stage, in which the glaciers reached particularly low locations due to spe- cial favourable aspects such as north-exposure, steep and narrow gorges, high shading and considerable snow accumulation. This is also valid for the sidebranches of the Slovenian Koritnica valley which are again directed west-east. Still younger glacier stages could be found in the upper sections of the Dogna, Raccolana and Bala valley. For the moraines of very low altitudes in the Resia valley, at the entrance to Mònica and the upper Raccolana valley pollen analyses are available. All considerations in the paper are estimations based on geomorphological and climatological experience. KEY WORDS: geomorphology, glacial, Gschnitz stadial, gorge-like valleys, high precipitation, moraines, kame terraces, pollen analysis The article was submitted for publication on May 26, 2010. ADDRESSES: Wolfgang Tintor, Ph. D. Korpitsch 26, A – 9587 Riegersdorf, Austria E-mail: wolfgang.tintoraaon.at Maja Andri~, Ph. D. Institute of Archaeology Scientific Research Centre of the Slovenian Academy of Sciences and Arts Novi trg 2, SI – 1001 Ljubljana, Slovenia E-mail: maja.andricazrc-sazu.si 8 Acta geographica Slovenica, 54-1, 2014 1 Introduction 1.1 General facts concerning the Lateglacial After the rapid decay of the high-glacial ice stream-net and the piedmont lobes about 21,000–19,000 years ago a transitional era followed with several halts and readvances which were named the »Alpine Lateglacial« by Penck and Brückner (1901/1909). Large parts of the Central Alps were deglaciated, even if still big systems of dendritic glaciers existed which filled especially the longitudinal valleys of the Inn or Drau (van Husen 2000). The oldest stadials were named after the classical type localities »Bühl« and »Steinach« (Heuberger 1968); in the latter stage the main valleys were already free of ice and the glaciers had retreated into the tributary val- leys (van Husen 2000). After a marked cooling phase the »Gschnitz« readvance occurred with large blocky ridges (Ivy-Ochs et al. 2005). With well-defined, often sediment-rich moraines from cirque and smaller val- ley glaciers the »Senders« stadial followed with its type locality being situated in the rear part of the Stubai valley (Kerschner 1986). Likewise in the Stubai valley both of the youngest readvance phases, »Daun« and »Egesen« were discovered with little accentuated moraines showing solifluction overprint for the older phase. However, the Egesen stage contains sharp-crested, often blocky ridges mostly at the foot of cirques (Ivy-Ochs et al. 2005). With the exception of the Egesen readvance which was dated in the Younger Dryas (11,000–10,000 BP) the absolute ages of the individual stadials are still unclear; according to a recent paper the Gschnitz stadial can be classified to 15,400 ± 1400 BP (Ivy-Ochs et al. 2005). Regarding the temperature conditions in the Bühl and Steinach stage little more is known than estimated values; for the Gschnitz stadial, however a lowering of the summer temperatures was calculated with 8.5–10.0°, whereas for the Younger Dryas they were only 3.5–4.0 °C lower than modern values (Ivy-Ochs et al. 2005). Considering the more maritime external areas of the Alps, to which the Julian Alps are counted, the low- ering of the mean annual air temperature in the Tyrolean Alps was calculated with 4.1° for the Senders stadial, with 3.5° for the Daun stadial and with 2.9° for the Egesen stadial (Kerschner 1985). Different from the still drier Central Alps in the Lateglacial the more oceanic Southern Alps received about the same amounts of precipitation as today (Kerschner 1985). The impact of two of the coldest stadials – Gschnitz and Egesen – also affected the vegetation com- position: with climatic warming after the Gschnitz stadial afforestation progressed and the treeline in northern Italy shifted to 800–1000 m (Vescovi 2007). This trend even increased at ca. 14,800–14,400 and 13,800 cal. BP with a change in forest composition and density having more broadleaved trees. The results of the vegetation: the landscape in the Alps was open with predominantly herbaceous plants (Vescovi 2007, Andri~ 2009). These palaeoenvironmental conditions also had a significant impact on the formation of the lateglacial glaciers in the Julian Alps. 1.2 Research area This paper presents the continuation of an essay on the Lateglacial in the northern valleys of the Italian Julian Alps (Tintor 2005) and is based on a very detailed glacial-morphological treatise on the catchment of the Fella (Desio 1927). The research area is framed by the western Val Canale from Ugovizza to Pontebba where it turns south, runs through the Canal del Ferro, bends westward close to Chiusaforte and reaches the Resia valley at Resiutta. East of Passo di Predil (1156 m) the article also dealt with the 15 km long Koritnica valley which belongs to Slovenia and runs into the So~a valley in the Bovec basin (figure 1). The research area comprises about 360 km2. The Val Canale lies at an altitude of 770 m in Ugovizza, however at only 568 m in Pontebba and just 315 m in Resiutta. The Dolina Koritnica reaches only 430 m near Bovec; this expresses how low the local base of erosion is in the western and and southern valleys of the Julian Alps. The altitude difference is often higher than 2000 m at a horizontal distance of only 5 km: Montasio is 2200 m above the Dogna and Raccolana valleys, Canìn is 2090 m higher than the Resia valley and Mangart is 2040 m higher than the Koritni{ka valley (Tintor 1993). This precipitous relief together with the enormous precipitation cause extraordi- narily high morphodynamics with landslides, mudstreams, debris amount and a strong notching and ramification into tributaries, especially in the western valleys. These facts show clearly that large parts of the valleys do not or cannot contain lateglacial moraines any longer as they were eroded. 9 Wolfgang Tintor, Maja Andri~, Lateglacial studies in the western valleys of the Italian Julian Alps and in the Koritnica valley The recent conditions of precipitation – they may have been very similar in the Lateglacial – should be dealt with in greater detail: in the Resia valley on average 2700–3000 mm are recorded annually and in Bovec 2840 mm (1951–1980). This precipitation situation may be compared to an extra-alpine and Mediterranean region, the Durmitor area in Montenegro where the calculated precipitation on the highest parts amounts to about 2600 mm (Djurovi}, 2009; 2012). Very favourable for glaciation is the annual course of precipita- tion influenced by the Mediterranean Sea with the main peak in autumn and the secondary one in spring; it can be assumed that in the Lateglacial most of the precipitation fell in the form of snow. On Sella Nevea two metres of snow are not unusual in wet winters. Finally it must be emphasized that particularly in the lee of W–E directed ridges and crests most of the snow was deposited; this can be considered the reason that today two small glaciers still exist in a low position at the foot of the north faces of Canìn and Montasio. 2 The Lateglacial in the individual valleys 2.1 Dogna valley Because of the deeply notched and narrow valley bottom terminal moraines are missing entirely in the Dogna valley; they must have been eroded rapidly, while many lateral moraines were found. In the lower section 0 5 10 km Research area Settlement State border Peak Lake, river Pass Sources: Carta stradale della regione autonoma Friuli-Venezia Giulia, Tabasco; Atlas Slovenije, Mladinska knjiga Author of the content: Wolfgang Tintor, Author of the map: Tamara Korošec Figure 1: Research area, its surroundings and sites of lateglacial moraines. 10 Acta geographica Slovenica, 54-1, 2014 on the still more easily accessible north side four smaller ridges were found of which two at a time cor- relate in their altitude (770 m below Chiout Zucuin and 730 m a bit W of Chiout di Gus; 950 m on the slope Culas above Chiout Zucuin and 920 m at the pasture Tassót). The ice thickness can thus be determined to 410 m at the utmost for the upper moraines and to 220 m for the lower ones (probably Bühl stage). Regrettably no certain indications could be found for the Steinach stadial in the entire valley, where- as the Gschnitz stage has left very clear marks, particularly on the southern valley flank. If you follow the marked path no. 640 well-rounded triassic boulders can be found close to house ruins on the former pasture Costa di Goliz (650 m); a near-terminus lateral moraine can be seen up to 720 m, above which erratics are found up to 800 m. Beyond the hard passable Sfonderat gorge after another brook notch you get to the rock ledge refor- ested pasture Granvalt where at 660 m there are situated two well-formed lateral moraines (Desio 1927). Here the valley bottom consists of yellow marl limestones of the Raibl strata; so the numerous triassic boulders on the opposite valley side stand out against those particularly well. At 630 m just below the road there is the largest erratic block consisting of light Dachstein limestone showing that presumably a very steep Gschnitz glacier fed primarily by avalanches flowed a short distance out of the Sfonderat gorge into the Dogna valley. Very similar conditions will have prevailed in the adjacent Rondolon gorge where howev- er no moraines could be found, just some erratics here and there. The snowline calculated just overviewingly Bühl Gschitz Senders Daun Egesen 0 5 10 m Rocks, ridge Palynological sampling sites State border Lake, river Sources: Carta stradale della regione autonoma Friuli-Venezia Giulia, Tabasco; Atlas Slovenije, Mladinska knjiga Author of the content: Wolfgang Tintor, Author of the map: Tamara Korošec Figure 2: Presumable stadials of the moraines and palynological sampling sites 11 Wolfgang Tintor, Maja Andri~, Lateglacial studies in the western valleys of the Italian Julian Alps and in the Koritnica valley ROTIN TGNAGFLOW Figure 3: Gschnitz moraine cut by the Dogna stream toward Clapadorie gorge; position Dogna Road. for both of the gorge glaciers would result in 1300–1400 m (method Höfer) which is low for the Gschnitz stadial and can only be explained with the particular topographical position. The side gully of Rio Saline following in the east is the widest of all north facing gullies in the Dogna valley. Its Gschnitz glacier reached a length of 4.5 km and its near-terminus lateral moraines west of Colle Fratte are impressive accumulations up to a height of 20 m (Desio 1927). The snowline determined with 1480 m corresponds fairly exactly to that for the somewhat longer Gschnitz glacier in the Val di Rio Freddo (Tintor 2005). The uppermost and very last side gorge in the Dogna valley is the already mentioned Clapadorie. Its glacier pushed up two marked near-terminus lateral moraines at its right side. The snowline of this glac- ier fed exclusively by drifted snow and avalanches was calculated for 1520 m (figure 4). On the Somdogna pass there is a wide and 500 m long ridge on its southernn side showing a small pond at its inner side (Il Laghetto, 1442 m). Most probably in the Senders stage a largely debris-covered glacier must have come down there into the soft marl limestones of the Raibl layers at the pass. The snow- line of the 900 m long cirque glacier was at 1630 m, which is strikingly low, but that should be caused by the north–east exposure and the steep relief of the lower glacier half. At the lower end of the small cirque of Jof di Somdogna you find a terminal moraine (1620 m) whose 500 m long glacier was very shallow in its snout area and may be assigned to the Daun stadial. 2.2 Raccolana valley In this narrow mountain valley with frequently vertical rock walls there are only few lateglacial moraines; near its lower end in a flat area of Stavolo Bilizzis (558 m) many light, rounded triassic boulders can be 12 Acta geographica Slovenica, 54-1, 2014 Sources: Carta stradale della regione autonoma Friuli-Venezia Giulia, Tabasco; Atlas Slovenije, Mladinska knjiga Author of the content: Wolfgang Tintor, Author of the map: Tamara Korošec 46° 28’ Gschnitz moraine Gschnitz moraine uncertain 25 m – contour line Stream Bog 0 200 400 m Road 19° 24’ Figure 4: Gschnitz moraines in the upper Dogna valley. found; most probably they have to be assigned to the Bühl stadial as they belong to a small lateral ridge high above the valley bottom. In this phase the Raccolana glacier must have been 140 m thick. The impressive Patòc moraines (785 m) on the sunny side above Chiout Michel are Bühl-lateral moraines indicating a glacier with a thickness of 300 m. From here a small and shallow branch (20–25 m thick) flowed down the Patòc valley. Like in the Dogna valley Steinach moraines are missing completely here as well; it can be concluded that in this stadial most of the Raccolana valley was filled with ice. This also implies that the massive kame terraces in the valley must be of younger age. 80 m above the valley floor (Plan Moras) a 2.5 km long gorge glacier flowing down the Sbrici ravine pushed up a near-terminus lateral moraine; due to its location at the confluence of a side gorge it must 13 Wolfgang Tintor, Maja Andri~, Lateglacial studies in the western valleys of the Italian Julian Alps and in the Koritnica valley have been a Gschnitz glacier. The snowline calculated roughly resulted in 1250 m which is a very low value. The very steep and narrow gorge glaciers in this valley had all in common that they lay far below the cli- matic snowline even at that time. The two kame terraces following up the valley, at Tamaroz and W of it with flat areas in 600–620 m will have been dammed by a north-facing hanging glacier from Cresta Indrinizza and by a small S fac- ing ice stream from Monte Cimone. From the very steep Vallone Blasic another glacier must have run down in the Gschnitz stadial. Today only some ice-abraded rock zones in the steep tributary give evidence of it and also the fine sediments dammed at its lowest margin when the glacier blocked the valley bottom tem- porarily. The snowline of the 3 km long glacier will have been at an altitude of 1400 m. Up the valley on a hill similar to a ridge a sediment sample for a pollen analysis was collected and the results (table 1) showed that pollen grains are present in very low concentration, whereas the percentage of degrad- ed pollen is high (20%) suggesting a selective degradation of pollen grains. Of the preserved tree pollen birches, pines and spruces predominated; as in the vicinity of the digging zone there are many beeches and many roots in the uppermost layer of the soil there could have been a contamination with recent beech pollen in the sample (table 1). Even so doubts remain if this formation really is a moraine of the Gschnitz stadial. It could also be an atypical postglacial debris flow and is therefore not contained in figure 2, but the sites of the samples are marked with A–C. In any case the glacier belonging to it would have been 4 km long down from Sella Nevea whereas the main glacier flowing NE into Valle Rio del Lago still reached a length of 8.5 km in that stadial. During a hiking tour on the N declivity of Canìn a small lateral moraine was found in Foran dal Muss at 1850 m; due to its high altitude it may be assigned to the Egesen stadial. Another one was found at the turn-off of the track to Sella Blasic (1950 m). On the sunny Montasio side a terminal moraine could be detected at the lower end of the small Palone cirque; in its W part (2090 m) it is already covered by ROTIN TGNAGFLOW Figure 5: Fine sediments of a kame terrace east of Vallone Blasic; position Raccolana road. 14 Acta geographica Slovenica, 54-1, 2014 Table 1: The results of pollen analyses are presented as the number of pollen grains counted in each sample. In brackets the percentage of each pollen type was calculated on the basis of pollen sum of all taxa (without degraded pollen); see figure 2 for the position of the study sites. Val Resia San Giorgio Dolina Koritnica Mònica Val Raccolana 460 m-A 530 m-B 655 m-C Pinus (pine) 145 (35.9%) 40 (20.3%) 6 (8.6%) Picea (spruce) 24 (5.9%) 36 (18.2%) 5 (7.2%) Betula (birch) 5 (1.2%) 26 (13.1%) 14 (20.2%) Fagus (beech) – 4 (2.0%) 6 (8.6%) Alnus (alder) 2 (0.4%) 1 (0.5%) 3 (4.3%) Corylus (hazel) 10 (2.4%) 2 (1.0%) 6 (8.6%) Carpinus b. (hornbeam) – 1 (0.5%) 3 (4.3%) Salix (willow) 1 (0.2%) – – Fraxinus o. (ash) – – 1 (1.4%) Poaceae (grass) 8 (1.9%) 11 (5.5%) 9 (13.0%) Cyperaceae (sedge) 11 (2.7%) 2 (2.0%) – Chenopodiaceae (goosefoot) – 1 (0.5%) – Compositae lig. (dandelion family) 22 (5.4%) 23 (11.6%) 7 (10.1%) Filicales (monolete fern spores) 171 (42.4%) 22 (11.1%) 9 (13.0%) Trilete spores (trilete fern spores) 3 (0.7%) 23 (11.6%) – Selaginella (clubmoss) 1 (0.2%) 2 (1.0%) – Thelypteris pal. (marsh fern) – 2 (1.0%) – Indet. degraded (indetermined, 16 (3.9%) 16 (8.1%) 14 (20.2%) degraded pollen) Pollen sum 403 197 69 pollen concentration 6378 1109 406 no. of grains/1 cm3 a recent debris slope, however towards E it is well marked and climbs up to 2125 m there. The little glac- ier will have occupied an area of 0.95km2; together with the glaciated flanks at the foot of Modeon del Montasio it amounted to 1.5 km2. In the spacious Cregnedul cirque a distinct terminal moraine of the Egesen stadial (2030 m) could be discovered; the glacier belonging to it had an area of 1.2 km2. Following to E at the foot of Forcella Lavinal dell' Orso there is a striking terminal moraine at an alti- tude of 1990–2030 m; its Egesen glacier facing E amounted to 0.94 km2 and has also to be attributed to the catchment of Valle Rio del Lago. Interestingly the terminal moraines of the same stadial in the region of Mt. Durmitor (Montenegro) are also situated at an altitude of ca. 2000 m, some in the west even at 1800 m (Djurovi} 2009). 2.3 Resia valley The southernmost of the three valleys is at the same time the lowest one; even so the valley was consid- erably glaciated in the Lateglacial because of the excessively high precipitation. At Stavoli Ruschis 10–20 m high lateral moraines were discovered (crest height 697 m) which can be assigned to the Bühl stadial with a high degree of certainty; at that phase the Resia glacier was still 330 m thick there. Another Bühl moraine was found E of Prato di Resia at the ruins of the pasture Bükvica (705 m); here, too the glacier was about 300 m thick. Two km east of Stolvizza some small moraines were discov- ered of which the corresponding ice thickness must also have amounted to 300 m and possibly 390 m for an older Bühl phase. The moraine complex immediately E of the Calvary of Resiutta is bent convexly, about 400 m long, reaches 402 m in its highest point and must have been pushed up by a 4.5 km long glacier from the trib- utaries of Rio Resartico and Rio Serai. There a snowline of only 1070 m can be assumed. Apart from the very high quantities of snow again the great inclination, the north exposure, the narrow gullies and the slopes towering highly and steeply to east which counteract the intensive solar radiation, can be seen as supportive to glaciation. Besides the ridge from Monte Plauris to the Cime del Monte Musi as well as the valleys south 15 Wolfgang Tintor, Maja Andri~, Lateglacial studies in the western valleys of the Italian Julian Alps and in the Koritnica valley and north of it still receive the highest annual precipitation of the Alps (Musi/Muzci 3313 mm, Coritis 2939 mm).This can also be assumed for the lateglacial climate in this region (Tintor 1993). Only 4.5 km upstream and 50–80 m higher the largest moraines of this study area can be found: the 3.5 km long, mighty and blocky terminal moraines (440–465 m) of San Giorgio were attributed part- ly to fluvioglacial processes (Desio 1927). They correlate with the near-terminus lateral moraines on the other side of the stream at Gniva which can be followed up to 570 m. They were accumulated by a 5 km long tributary glacier from the Barmán valley in which you come across the next terminal ridges already after 2 km. Most probably they represent the second phase typical for the Gschnitz stadial and are again blocky. The snowline of this impressive ice stream was situated at 1130 m which again was only possible due to the special factors mentioned above. From the San Giorgio moraine a sediment sample was taken for a pollen analysis: 35.9% were pine pollen, only 5.9% spruce, 1.2% birch, ca. 2.7% sedge, but also 42.4% monolete fern spores (Filicales, table 1). Although these results are well comparable with the pollen record of the Gschnitz moraine at the lower Fusine lake (Tintor 2005), they do not permit the authors a very detailed datation of the moraine. But together with the morphological diagnosis it should be sufficient to classify both sit- uations to the Gschnitz stadial. In the upper valley section notching in side gullies and small ravines increases sharply, frequently you come across kame terraces, of which one of the largest is that of Huda Raven, southeast of the confluence of Rio Ronch; at its southeastern side (564 m) it is incised by Rio Secco and exposed in several decame- tres, in which you can observe an alternating deposition of coarse material and fine sediments (figure 6): The kame terrace is 50–60 m thick and was formed supposedly in the Gschnitz stadial at the margin of a glacier which flowed 4.5–5 km long from the S and W facing flanks of Picco di Grubia, Picco di Carnizza and Canìn. Its snowline must have been in 1430–1450 m which in view of the high precipitation at the Kanin/Canìn ridge is not so low. ROTIN TGNAGFLOW Figure 6: Up to 60 m high and 400 m long opening with sand and gravel of the kame terrace Huda Raven in the upper Resia valley; position Rio Secco. 16 Acta geographica Slovenica, 54-1, 2014 2.4 Koritnica valley and tributaries The Koritnica valley shows a well-formed lateral moraine (720 m) on its western side immediately above the main village Gorenji Log pod Mangartom; it can be assigned to the Bühl stadial due to its altitude above the valley bottom. The glacier will have had a thickness of ca. 80 m in this part of the valley. [ifrer and Kunaver (1978) mentioned six different end moraines only for Lo{ka Koritnica which could not be verified. In the upper part of Koritnica two unambiguous and blocky glacial deposits were found: the lower one is situated in an altitude of 860–865 m close to the abandoned farm Ganza and the upper, more marked one in 940–950 m. These should be the two phases of the Gschnitz stadial, but interestingly the glac- ier was hardly more than 3 km long here and ended fairly high. Accordingly high also the snowline of 1580 m – at an assumed mean altitude of the ridges framing the glacier with 2300 m. The uppermost valley is exposed to the sun and furthermore the precipitation in the Lateglacial must have decreased rapidly from the out- ward ranges in the south toward north similar to the present time which was also decisive here (Tintor 1993). The 5 km long, deeply notched side valley of Mònica is terminated at its southern side by the ridge from the Confin peak to Rombon; at the lower end of the valley there is a mighty, wide and 60–70 m high terminal moraine (max. 590 m) which the stream cuts through meanderingly in a narrow gorge. On both sides two near-terminus lateral moraines run down steeply implying that the glacier in between was still 550 m wide and could have dammed the Koritnica river at least in the first Gschnitz phase (figure 7). A lat- eral moraine was found at 800 m by geologists who also reconstructed the glaciers of the Koritnica and So~a valley for a stadial not mentioned by modelling (Bavec 2004); so their climatic snowline calculated for the whole area bears no relation to the orographical snowline of our local glaciers. A sample taken from the lower part of the moraine (530 m) produced a meaningful result with a high percentage of tree pollen (table 1); the pollen record itself allowed only a wider (presumably Lateglacial) ROTIN TGNAGFLOW Figure 7: Moraine complex (centre and lower half of the picture) at the confluence of Mònica into the Koritnica valley. 17 Wolfgang Tintor, Maja Andri~, Lateglacial studies in the western valleys of the Italian Julian Alps and in the Koritnica valley temporal determination but the following additional factors also speak in favour of the Gschnitz stage in spite of the low location: the strong shading of the lateglacial glacier by the Rombon ridge in the south, the maximum zone of precipitation on this very ridge and connected with that the high snow accumu- lation in the immediate leeward side to the N of it, the special height of the moraine itself as well as the lack of other moraines in the more spacious area between 800 and 900 m in which for example in the northern valleys of the Julian Alps Gschnitz moraines are situated in large numbers. The snowline for the Mònica glacier amounted to a rather low value of 1250 m. The morphological map of [ifrer and Kunaver (1978) and a later paper (Kunaver 1990) describe six different end moraines for Bav{ica and the Bala valley which could not be verified. The lowest, blocky ter- minal ridge is at 700 m; 500 m up the valley you discover the next end moraine (figure 2). The glacier flowing down the Bala valley to Bav{ica was 6.5 km long, a second southern tributary ice stream from Bav{ki Grintavec had a length of 3.5 km (table 2). The mean altitude of the peaks and ridges framing the lateglacial ice streams can be assumed with 2200 m here which means a snowline of 1450 m. Kunaver (1990) assumes a Bühl stadial for these frontal moraines; however, they are too well preserved, arranged in two phases immedi- ately behind each other and moreover, located in a tributary, not in the main valley. In the area of Planina Bala alp just a valley step with debris slopes could be found but by no means an accumulation of glacial deposits. Only at an altitude of 1400 m you come across a small ridge which is a debris-rich accumulation, possibly belonging to the Senders stage; the glacier of this stadial was just 2 km long and its snowline was thus situated at 1800 m. In a horizontal distance of about 700 m and at an altitude of 1560–1600 m you find another glacial proof which was pushed up by a small cirque glaci- er with a length of about 1.3 km and presumably it can be assigned to the Daun stadial. Table 2: Front altitude (in m) and length (in km) of glaciers of the presumable Gschnitz stadial in the individual valleys. Dogna Raccolana Resia Koritnica Sfonderat (600/3,0) Saline (750/4,5) Clapadorie (830/3,5) Somdogna 950/2,5 Sbrici (500/2,5) Blasic (560/3,5) Monte Plauris 400/4,5 Barmán 440/5,0 Ronch (560/4,5) Koritnica 860/3,0 Mònica 520/5,0 Bav{ica/Bala 680/6,5 ( ) – values = estimated, without terminal moraines 3 Conclusions All glaciers of the presumable Gschnitz stadial mentioned in this paper belonged without exception to the avalanche basin type without an actual accumulation area. All glaciers were strongly subordinate to the relief and were covered highly with debris, particularly the one streaming down from the Barmán val- ley, a north-facing tributary of the Resia valley and the Mònica glacier whose terminal moraines are exceedingly mighty. Of the twelve lateglacial glaciers listed up in table 2 seven were north- or north-west-facing, three direct- ed to southwest and one each was east- and south-southeast-facing. The lowest one was that ice stream flowing down from Monte Plauris to the lowest part of the Resia valley (400 m altitude of the front moraine), the highest one the small Somdogna glacier (figure 4), where it is no coincidence that the first was situ- ated leeward of the ridge with the highest precipitation at the southern verge of the Alps and the latter one in the northernmost and therefore drier valley. The southern periphery of the Julian Alps is still consid- ered to be the wettest part of the Alps. As described in the preceding chapters most glaciers owed their low 18 Acta geographica Slovenica, 54-1, 2014 position also favourable topographical aspects like the present Montasio glacier, a narrow gorge glacier with its snout at 1880 m; therefore their local orographical snowline was far below the climatic snowline. The precipitation increasing to the S margin of the mountains corresponds with the snowline decreas- ing from north to south; it amounted to an approximate altitude of 1500 m on average of three glaciers for the N valleys (Tintor 2005); in the Dogna valley the mean value was just 50 m lower followed by the only insignificantly more southern Koritnica valley with 1430 m on average. The snowline in the Raccolana valley may have been 1325 m on average of only two very steep gorge glaciers which means another low- ering of more than 100 m. Likewise in the Resia valley it must have been located another 110 m lower, that is at 1210 m on average. The straight line from the lateglacial front moraines of the N valley glaciers to those of the Resia valley amounts to just 15–19 km; the precipitation averaged from four stations each increases, however by 1000 mm at this distance according to present conditions (Tintor 1993). Thus also in this mountain range the importance of the precipitation can be expressed as the crucial parameter for glaciation along with the temperature and the relief. 4 Acknowledgements The authors would like to thank Prof. Giovanna Meneghel from the Dipartimento di Economia, Società e Territorio of the university of Udine for her assistance in finding the geological maps. Furthermore we thank Mag. Dr. Irena Mrak from the department of geography of the university of Ljubljana for the pro- vision of two older papers on the So~a and the Koritnica valley. Besides the author is grateful to his friend Erich Wipfler for accompanying him to the Sfonderat gorge in the Dogna valley. For the graphic arrange- ment of the figures we are indebted to Mrs. Timea Marekova and Mrs. Tamara Koro{ec. We are also grateful to Dr. Milo{ Bavec and an anonymous reviewer for their comments on the first draft of the paper. 5 References Andri~, M., Massaferro, J., Eicher, U., Ammann, B., Leuenberger, M. C., Martin~i~, A., Marinova, E., Brancelj, A., 2009: A multi-proxy Late-glacial paleoenvironment record from Lake Bled, Slovenia. Hydrobiologia 631-1. Assereto, R., Comizzoli, G., Passeri, L. D., 1964: Carta geologica 1 : 100 000 – Foglio 14A. Tarvisio Trieste. Bavec, M., Tulaczyk, S. M., Mahan, S. A., Stock, G. M., 2004: Late Quaternary glaciation of the Upper So~a River Region (Southern Julian Alps, NW Slovenia), Sedimentary Geology 165-3–4. Bennet, K. D., Willis, K. J., 2002: Pollen. Tracking environmental changes using lake sediments 3. Dordrecht. Cobertaldo, D., Gortani, M., Selli, R., 1949: Carta geologica delle tre Venezie 1 : 100 000– Foglio 14, Pontebba – Trieste. Desio, A., 1927: L'evoluzione morfologica del bacino della Fella in Friuli. Atti della Società Italiana di Scienze Naturali e del Museo Civico di Storia Naturale di Milano 65-3–4. Djurovi}, P., 2009: Reconstruction of the pleistocene glaciers of Mount Durmitor in Montenegro. Acta geographica Slovenica 49-2, Ljubljana. DOI: http://dx.doi.org/10.3986/AGS49202 Djurovi}, P. 2012: The Debeli Namet glacier (Durmitor, Montenegro) – from the second half of the 20th cen- tury to the present. Acta geographica Slovenica 52-2. DOI: http://dx.doi.org/10.3986/AGS52201 Dollinger, F., 1986: Überlegungen zur spätglazialen Vergletscherung des Höllengebirges/Nördliche Kalkalpen/Oberösterreich. Zeitschrift für Gletscherkunde und Glazialgeologie 22-2. Fritz, A., Ucik, F. H. 2002: Eine unerwartete neue Deutung der Klima- und Vegetationsgeschichte des mit- teleuropäischen Spätglazials. Mitteilungen der Österreichischen Geographischen Gesellschaft 144. Fritz, A., Ucik, F. H. 2003: Das Gailtal (Kärnten) – Ein ostalpines Gehölzrefugium seit dem Ende des Würm-Hochglazials: Pollendiagramm Görtschach. Mitteilungen der Österreichischen Geographischen Gesellschaft 145. Furrer, G., Burga, C., Gamper, M., Holzhauser, H. P., Maisch, M. 1987: Zur Gletscher-, Vegetations- und Klimageschichte der Schweiz seit der Späteiszeit. Geographica Helvetica 42. Gams, I. 1992: Prispevek k mladokvavtarni geomorfologiji v zgornjesavski dolini. Geografski zbornik 32. Hambrey, M. Alean, J. 1992: Glaciers. Cambridge. 19 Wolfgang Tintor, Maja Andri~, Lateglacial studies in the western valleys of the Italian Julian Alps and in the Koritnica valley Heuberger, H. 1968: Die Alpengletscher im Spät- und Postglazial. Quarternary science 19-1. DOI: http:/ dx.doi.org/ 10.3285/eg.19.1.24 Ivy-Ochs, S., Kerschner, H., Kubik, P. W., Schlüchter, C. 2006: Glacier response in the European Alps to Heinrich Event 1 cooling: the Gschnitz stadial. Journal of Quaternary science 21. DOI: http://dx.doi.org/ 10.1002/jqs.955 Kerschner, H., Berktold, E. 1981: Spätglaziale Gletscherstände und Schuttformen im Senderstal, Nördliche Stubaier Alpen, Tirol. Zeitschrift für Gletscherkunde und Glazialgeologie 17-2. Kerschner, H. 1985: Quantitative palaeoclimatic inferences from lateglacial snowline, timberline and rock glacier data, Tyrolean Alps, Austria. tschrift für Gletscherkunde und Glazialgeologie 21. Kerschner, H. 1986: Zum Sendersstadium im Spätglazial der nördlichen Stubaier Alpen, Tirol. Zeitschrift für geomorphologie 61. Kerschner, H. 1993: Späteiszeitliche Gletscherstände im südlichen Karwendel bei Innsbruck, Tirol. Innsbrucker Geographische Studien 20. Kerschner, H., Ivy-Ochs, S., Schlüchter, C. 2002: Die Moräne von Trins im Gschnitztal. Geographiche Exkursionsführer Europaregion Tirol, Südtirol, Trentino 33-2. Kugy, J. 1953: Die Julischen Alpen im Bilde. Graz. Kunaver, J. 1975: H Geomorfolo{kemu razvoju Bov{ke kotline v Pleistocenu. Geografski vestnik 47. Ljubljana. Kunaver, J. 1990: Poznoglacialne morene v najvi{jih delih poso{kih Julijskih Alp in poskus njihove dat- acije. Zbornik referatov, 5.znanstveno posvetovanje geomorfologov Jugoslavije. Lieb, G. K. 1987: Zur spätglazialen Gletscher- und Blockgletschergeschichte im Vergleich zwischen den Hohen und Niederen Tauern. Mitteilungen der Österreichischen Geographischen Gesellschaft 129. Maisch, M., 1982: Zur Gletscher- und Klimageschichte des alpinen Spätglazials. Geographica Helvetica 37. Melik, A. 1954: Slovenski alpski svet. Ljubljana. Moore, P. D., Webb, J. A., Collinson, M. E., 1991: Pollen Analysis. Oxford. Patzelt, G., 1975: Unterinntal – Zillertal – Pinzgau – Kitzbühel. Spät- und postglaziale Landschaftsentwicklung. Tirol, ein geographischer Exkursionsführer 2. Penck, A., Brückner, E. 1909: Die Alpen im Eiszeitalter. Leipzig. Reille, M., 1992: Pollen et Spores d'Europe et d'Afrique Du Nord. Laboratoire de Botanique Historique et Palynologie. Marseille. Reille, M. 1995. Pollen et Spores d'Europe et d'Afrique Du Nord (Supplement). Laboratoire de Botanique Historique et Palynologie. Marseille. [ifrer, M., Kunaver, J., 1978: Poglavitne zna~ilnosti geomorfolo{kega razvoja zgornjega Poso~ja. Zgornje Poso~je: zbornik 10. zborovanja slovenskih geografov. Ljubljana. Stockmarr, J. 1971. Tablets with spores used in absolute pollen analysis. Pollen et spores 13. Paris. Tintor, W. 1993: Die Kleingletscher der Julischen Alpen. Carinthia 103–183. Tintor, W. 2002: Überlegungen zum Spätglazial zwischen Fusine und Rate~e sowie im Mangarttal (Julische Alpen). Schriften der Geographie und Raumforschung 38. Tintor, W. 2005: Zum Spätglazial in den nördlichen Tälern der italienischen Julischen Alpen. Carinthia 115–195. Van Husen, D. 1977: Zur Fazies und Stratigraphie der jungpleistozänen Ablagerungen im Trauntal. Jahrbuch Geologische Bundesanstalt, 120/1. Van Husen, D. 1988: Zur quartären Entwicklung in Kärnten. Kärnten – Naturwissenschaftlicher Verein Kärnten, Klagenfurt. Van Husen, D. 2000: Geological Processes during the Quaternary. Mitteilungen der Österreichischen Geographischen Gesellschaft 92. Vescovi, E., Ravazzi, C., Arpenti, E., Finsinger, W., Pini, R., Valsecchi, V., Wick, L., Ammann, B., Tinner, W. 2007: Interactions between climate and vegetation during the Lateglacial period as recorded by lake and mire sediment archives in Northern Italy and Southern Switzerland. Quaternary Science Reviews 26. DOI: http://dx.doi.org/10.1016/j.quascirev.2007.03.005 Winkler, A. 1931: Zur spät- und postglazialen Geschichte des Isonzotales (Südalpen). Zeitschrift für Gletscherkunde und Glazialgeologie 19. 20 Acta geographica Slovenica, 54-1, 2014, 21–40 DETECTION OF FORMER LANDFILLS IN GRAVEL PLAIN USING GEOMORPHOMETRIC ANALYSIS AND HIGH-RESOLUTION LIDAR DTM ODKRIVANJE PRIKRITIH ODLAGALI[^ ODPADKOV V PRODNI RAVNINI Z GEOMORFOMETRI^NO ANALIZO IN LIDAR DMR Mateja Breg Valjavec CEV JALA VGER B JAETAM Bumpy and wavy micro-terrain of former landfill in Ljubljana gravel plain. Grbinast in valovit mikro-relief nekdanjega odlagali{~a odpadkov na Ljubljanskem polju Mateja Breg Valjavec, Detection of former landfills in gravel plain using geomorphometric analysis and High-Resolution LiDAR DTM Detection of former landfills in gravel plain using geomorphometric analysis and High-Resolution LiDAR DTM DOI: http://dx.doi.org/10.3986/AGS54106 UDC: 911.2:551.43(497.451Lj. polje) 551.43:628.472.3(497.451Lj. polje) 628.472.3:528.8(497.451Lj. polje) COBISS: 1.01 ABSTRACT: The article represents the application of geomorphologic approach to discover the poten- tial areas of buried waste in agricultural landscape of Ljubljana gravel plain. Some former waste disposal sites or landfills are underground sites characterized by heterogeneous old waste buried in formerly con- cave landforms: old inactive gravel pits or paleo-riverbeds. They form different types of anthropogenic landforms. They were primary recognized and located with the terrain visualization (analytical shading, hypsometry) of LiDAR data and in continuation with geomorphometric analysis and classification of flu- vial terrain. Due to subsidence of heterogeneous waste, terrain of former landfill sites is bumpy and uncharacteristic of fluvial surface morfology or terrain. The geomorphometric analysis was applied to differentiate the anthropogenic landforms (gravel pits, filled gravel pits …) from natural alluvial landforms with combination of two geomorphometrics: multiresolution index of valley bottom flatness (MrVBF) and convergence index and high density LiDAR data. Result is the automatically derived classification of ter- rain in to three classes: (1) bumpy terrain, typical for areas with high terrain potential for landfill, (2) flat terrain, typical for dry paleo riverbeds and (3) »agricultural« terrain, typical for intensive fields and mead- ows. By comparing the results of geomorphometric analysis with the results of visual analysis the 26 of 46 visually detected anthropogenic landforms are overlapping the areas of high terrain potential for land- fill and among these 8 objects were proved with geohistorical analysis of archive aerial photographs. KEY WORDS: applied geography, landfill, gravel pit, paleo riverbed, visualisation technics, geomorphometry, LiDAR, DTM, Ljubljana gravel plain. The article was submitted for publication on January 14, 2013. ADDRESS: Mateja Breg Valjavec, Ph. D. Anton Melik geographical Institute Research centre of Slovenian academy of sciences and arts Novi trg 2, SI – 1000 Ljubljana, Slovenija E-mail: mateja.bregazrc-sazu.si 22 Acta geographica Slovenica, 54-1, 2014 1 Introduction The main research objects are former landfills on Ljubljana gravel plain. These are underground objects characterized with heterogenous old waste being buried in once concave landforms. The results of pre- vious Slovene studies (Bricelj 1988; [ebenik 1994; Ku{ar 2001; Breg and Urbanc 2005; Breg et al 2007; Smrekar 2007 etc.) and some international studies (Silvestri in Omri 2008) showed that in the past the waste was often illegally disposed in natural (paleo river beds, sinkholes) or anthropogenic basins (gravel pits or other open mining pits). Regarding these the research is oriented in study of landfills in gravel pits and paleo riverbeds being among the most frequent concave landforms in the terrain of Ljubljana gravel plain. The main objective of this research is to show that landfills can be determined also by using geomorphic methods and LiDAR terrain data. Despite the remarkable accuracy and usefulness of LiDAR data can be theoretically determined only landfills, the consequences of which are visible in the LiDAR DTM, which applies to landfills that were not adequately covered with a thick layer of fertile soil, which would allow intensive farming. At these landfills intensive agricultural land use and production is not present, but mead- ows and reforestation, which is reflected in the micro-terrain and in texture of shaded terrain. Many researchers attempted to identify buried waste by using various techniques of remote sensing and multispectral satellite data. They were focusing on degraded vegetation and soil pollution. Detailed review of past remote sensing researches is available in Silvestri and Omri (2008), Slonecker et al (2010) and others. Almost none research has been done in terms of studying the effects on geomorphology result- ing from the landfilling of waste. Using Landsat TM and ETM satellite data or very higher spatial resolution remote sensing data (Quickbird, Ikonos, GeoEye1) also geomorphic changes in various geomorphic features, such as riverbed and shoreline migration, meanders and old riverbeds can be identified (Ghanavati et al. 2008). Podobnikar et al. (2008) showed that analysing DTMs with 25 m pixel resolution enables highlighting changes to the geomorphology and makes human impacts visible as they clearly noticed many anthropogenic landforms (road embankments, traffic infrastructure, filled sinkholes, active grav- el pits) on a karstic surface also with marking the differences between DTMs from different periods. By photogrammetric processing of the archive aerial photographs DTM of former landscape can be processed. By further comparison with DTM of recent landscape elevation differences may be calculated. Using this approach the number and extent of filled dolines was quantitatively analysed in Slovene Logatec karst polje (Breg Valjavec 2010). For the Bílina coal mine (Slovak Republic) the elevation data was obtained for dif- ferent periods and volumetric analysis was used to calculate the temporal terrain differences (volume of excavated minerals) completed during the selected years (Pacina and Weiss 2011). The research is focusing in smaller landfills that are able to be visualized on the LiDAR terrain and recognized as the anthropogenic landforms through discovering the terrain texture of »scars« that were created in landscape due to underground waste dumping. The idea to recognize landfills with geomor- phometric analysis of recent terrain became more realistic with the availability of high-density LiDAR data, development of digital geomorphometric methods and specific software. DTM, which is obtained from a laser cloud of points, reflecting even the smallest variation in the topography (from few centime- ter to some ten's centimeters), being a consequence of geomorphological and anthropogenous processes (Mlekù 2010), like the land use impacts in terrain. LiDAR allows observation traces, scars and finger prints of natural and anthropogenic processes on the Earth's surface (Komac 2009; Mlekù 2010). 2 Case study area Ljubljana plain in general represents a tectonic depression filled mainly with gravel and sand sediments. In fluvial terrain of the gravel plain several terraces (highest Pleistocene and the lower Holocene terraces) accompany the main River Sava (Radinja 1951; [ifrer 1969). By moving river current from old into new riverbed paleo riverbeds have formed. In the recent landscape these are longitudinal slightly concave land- forms that can be identified as lowering's in terrain, especially in the lower Holocene terraces. Regarding this the study area was narrowed down to Holocene terrace. Study area (Figure 4) represents suburban belt (villages) on the northern part of Ljubljana that is interconnected with agricultural countryside (mead- ows and fields) and young forest vegetation along the River Sava. The areas in the immediate vicinity of cities were and are still impacted by illegal waste dumping (Breg and Urbanc 2005). Due to the gravel sediments, 23 Mateja Breg Valjavec, Detection of former landfills in gravel plain using geomorphometric analysis and High-Resolution LiDAR DTM the wider area of Ljubljana plain has always been interesting for gravel extraction especially near Sava River. Many medium-size gravel pits (from 1,000 to 5,000 m2) were partially or completely filled with waste and turned into » waste pits« (Breg and Urbanc 2009). 3 Methodology and LiDAR data The methodology is based on geomorphologic approach that determines landfill areas on the basis of flu- vial terrain characteristics and determination of anthropogenic landforms. It consists of two recognition methods based on DTM data: (1) visualization technics (analytical shading and hypsometry) and (2) geo- morphometric analysis. It is possible to determine the landform types with greater certainty with several different methods compared to each other (Cigli~ and Gostin~ar 2011). Numerical (geomorphometric) as well as visual analysis of DTM enables the recognition of landforms, such as ridges, picks, valleys (Podobnikar and Moìna 2008) and also anthropogenic landforms. The anthropogenic landforms were primary recognized and located with the terrain visualization of LiDAR data and in continuation with geomorphometric analysis and classification of fluvial terrain. The applied and analysed terrain data is LiDAR DTM (Lidar 2008, © GEOIN), based on data from laser scanning of 8 and 14 February 2008. Aerial survey was conducted by Optech Gemini LiDAR sensor. Primary data processing was done with Dashmap 5.3 and PosPac 4.4 software. For the final classification and treatment of the software package Terra Solid and MicroStation (Geoin 2011) was used. The cloud of points was divided into four classes of which we used class of points of the terrain.The terrain was smoothed by filling up the smaller »sinks« and analysed with visual and automated technics. Regarding land use types, only built up areas were excluded from geomorphometric analysis. 4 Visual analysis and characteristics of anthropogenic terrain of landfills The Lidar DTM was visualized so the terrain anomalies of an anthropogenic origin were located in the ter- rain of recent landscape. Regardless of the wide spectre of its uses, it is important to demonstrate (visualize) the DTM effectively, as it is the only assurance to guarantee the appropriate result interpretation. Despite several descriptions of advanced terrain demonstration, analytical shading remains one of the most com- mon methods (Zak{ek et al. 2010). Analytical shading (Figure 2 and 3) simply means a computer-assisted assembly of a shaded terrain from the DTM. The method, developed by Yoëli (1965), where the value of the grey is in correlation to the cosine of the ray's incidence angle of the direct terrain lighting, has become the standard. This is the angle between the direction towards the light source and the perpendicular line to the terrain surface. In this way, the areas perpendicular to the ray from the imaginary light source are white, and the areas with an incidence angle of 90° or more are in a complete shade or completely black, while the areas between an incidence angle between 0° and 90° are displayed with the appropriate grey or other color shade (Zak{ek et al. 2010). The hypsometry (Figure 1) is a visualisation technic that allows us to adapt the image histogram to our needs and expose the smaller landforms and micro-terrain char- acteristics (landfills). Both visualisation technics, analytical shading and hypsometry, were applied separated on the same LiDAR data sections (measuring 750 m × 500 m). By selecting smaller sections of DTM also the interval among minimum and maximum elevation values has narrowed. Smaller sections of gravel plain enable better color contrast in visualising flat terrain at local scale and to detect micro-terrain vari- ability and texture. With presented visualization methodology, we displayed DMR very precisely and reconstructed the old riverbeds in the agrarian landscape. We studied the natural terrain characteristics of fluvial terrain (paleo riverbeds) and anthropogenic landforms in order to determine geomorphic char- acteristics of landfills in filled basins. The essential geomorphic characteristic of paleo riverbeds are very low slopes at the bottom of the riverbed (under 0.5°) that quickly increase (for a few degrees) on the fold to the slope. The terrain anomalies were identified in the riverbeds that are a consequence of human activity and are shown as a con- vex landform (embankment), which interrupts the riverbed flow on a certain section of the river and can then continue on once more (Figure 1). The quality of visual recognition of convex anthropogenic land- 24 Acta geographica Slovenica, 54-1, 2014 Direction of paleo riverbed/ Direction of paleo riverbed/ potek stare struge potek stare struge Potential landfill inside paleo riverbed/ potencialno odlagališče v stari strugi Potential landfill inside paleo riverbed/ potencialno odlagališče v stari strugi 0 50 100 150 m Figure 1: Reconstruction of paleo riverbeds with visual analysis of DTM in different scales and detection of geomorphic anomalies. forms inside paleo riverbeds on LiDAR DTM depends on the size of study area. On the left image is taken zoomed view from visualization of 750 × 750 m study area and on the right image is taken zoomed view from entire area. Completely filled gravel pits do not particularly stand out in the terrain, as they were levelled with the surrounding terrain when they were filled. Since the waste may be very heterogeneous, it decays with different intensity. In accordance, a bumpy terrain is formed (Figure 2), which is untypical in the fluvial terrain of the alluvial plain. As the Latin name (Lat. Fluvio means river) designates, fluvial landforms are shaped by the movement of river water or in general when the laminar flow runs into a linear one due to its tendency to concentrate. For this reason, natural landforms in fluvial terrain are linear (valley, ravine, gorge, erosion channel and ridge). Bumpy landforms, typical for filled gravel pits, can be successfully studied on shaded terrain as wavy texture (Figure 2). Natural fluvial terrain of studied agrarian landscape is changed also due to the tradi- tional and intensive agricultural land use. By analyzing high resolution LiDAR DTM the effects of different land-uses can be recognized. This enables the classification of different types of land use from the geomorphological point of view. In the case of filled gravel pits dumped waste represents anthropogenic bedrock. In the formation of micro-terrain landforms in a completely flat terrain (gravel plain) play leading role landscape elements such as bedrock and in some cases also soil (soil depth), vegetation (tree roots), fauna (mole) and human. They can take the lead in geomorphological reshaping of flat terrain. Considering this, very similar bumpy micro-terrain was detected also in some other land use types: • forest that is growing on the shallow soils (rendzina) on paleo-gravelbeds near Sava River; • abandoned agricultural land inside extensive agrarian land, usually overgrown with bushes and trees, limited to the smaller strips or lots; • traditional meadow or pasture that include trees (Figure 3, green ring). 25 Mateja Breg Valjavec, Detection of former landfills in gravel plain using geomorphometric analysis and High-Resolution LiDAR DTM Landfill in the gravel pit/ nekdanje odlagališče v gramoznici 0 25 50 75 m Figure 2: Terrain of filled gravel pit is usually slightly convex and bumpy (black ring area). The terrain of surrounding fields is agriculturally altered due to the plowing and tillage of soil. Fluvial landform/ fluvialna reliefna oblika 0 50 100 m Figure 3: Micro-terrain that is shaped in traditional meadow (green ring) has very similar texture (micro-terrain) like the terrain of waste pit, used as a meadow (see Figure 2). 26 Acta geographica Slovenica, 54-1, 2014 Final dilema in separation between natural bumpy landforms and anthropogenic bumpy landforms (related to landfills) can be solved with geohistorical analysis of gravel pits, reconstruction of paleo riverbeds and field studies. With the visual analysis of DTM the 67 potential anthropogenic landforms related to excavation of gravel and waste dumping (Figure 4) were defined on a 5 km2 of case study surface. Landforms were divid- ed into four groups according to concavity / convexity, and potential for presence of buried waste (Figure 4): 1. Convex landforms are potential landfills if they are »overfilled« gravel pit or just a larger pile of dumped waste, expressly elevated above the surroundings. 2. Bumpy landforms (potential landfills): 2A. bumpy (slightly) convex micro-terrain, 2B. bumpy (slightly) concave micro-terrain, 3. Concave landforms are allegedly unfilled gravel pits or paleo riverbeds; Considering further geomorphomorphic analysis only convex (5), bumpy convex (24) and bumpy concave landforms (17) are potential landfills. Regarding this we can conclude that 46 objects have poten- tial to be landfill. 5 Geomorphometric analysis and results Geomorphometry is the science of topographic quantification; its operational focus is the extraction of land-surface parameters (terrain) and objects from digital elevation models (Hengl and Reuter 2009, Hrvatin and Perko 2009) or digital terrain models. The modern geomorphometry differs from classical quanti- tative geomorphology while it's specialized on computer characterisation and analysis of continuous topography (Hengl and Reuter 2009). The geomorphometric analysis is a second phase of our research and encom- passes determination of the potential areas that have the terrain characteristics typical for filled basins (landfills). The DTM can be automatically divided into classes with the use of geomorphometric parameters (the slope, curvature, level of incline curves, topographic openness, the accumulation of the water cur- rent) in order to determine landforms connected to fluvial processes (Anders et al. 2009). The Convergence index was used to exclude the converging areas, as they are not typical for the area of filled gravel pits with bumpy terrain and may also represent natural concave landforms (paleo riverbeds) and unfilled gravel pits. The module (in SAGA software) calculates an index of convergence/divergence regarding to the over- land flow. By its meaning, it is similar to a plan or horizontal curvature, but gives much smoother results. The calculation uses the aspects of surrounding cells, i.e. it looks to which degree the surrounding cells point to the center cell. The result is given as percentages; negative values correspond to convergent, pos- itive to divergent flow conditions. Furthermore, the areas of the flattened terrain were separated from the not Table 1: Joining the results of both geomorphometric indexes. Layer number Layer name Cell value Cell value Layer 1 + 2 Layer 1 Index of convergence / 0 (areas of converging, 1 (areas of divergence) divergence draining) CLASS 2 Layer 2 multiresolution index 0 (flat areas) 1 (bumpy, wavy terrain) 1 (flat but of valley bottom flatness anthropogenously CLASS 3 CLASS 1 altered terrain) Layer 1 + 2 0 (paleo riverbed) 2 (bumpy terrain) Figure 4: Spatial distribution of anthropogenic landforms which were recognized and classified by visual analysis of LiDAR terrain on study area Ljubljana plain. p p. 28 Figure 5: Geomorphometric classification of alluvial terrain. p p. 29 Figure 6: Comparison of two terrain methods (visualisation and geomorphometric analysis) and further improvements of results with geo-historical analysis (Breg Valjavec, Gostin~ar and Smrekar 2011). p p. 30 27 Mateja Breg Valjavec, Detection of former landfills in gravel plain using geomorphometric analysis and High-Resolution LiDAR DTM a: 410 2 ljevid aljavec UZA reg V SC ) ) rica zem R e 4 7 ateja B ZM lik y/avto M IA y b JE /Št. 2 /Št. 1 b G / L d o o © e o ap IN O tu area M A P S en L O g a (N a (N P o A SK p čen čen N N o o tro b JA JA L L izb v B B lo lo JU JU L L rsta an/v asta rah rm asta rah in ) fo ) in 0 d rb rb /Št. 5 /g /Št. 2o m ic lan o vex cave/g 0 en n n 0 g a (N a (N 4 op čen tly co tly co čen a IJA ro o h h o d b NE th /izb V 0 O egen f an y slig y slig 0 vex p p cave/v 2 /SL /L e o n m m n d p o u u o IA C B B C NE e ty V egen O L Th 0 SL 28 Acta geographica Slovenica, 54-1, 2014 m008 aljavec 0 v 0 reg V o 6 41 k 0 2 ad ateja B U p Z d a: M A 0 S 0 C 4 R ljevid lls/ ališče o Z fi relief M d lag IA d / jen čje en rica zem G r lan je o o 0 © m 02 an b d terrain rem o y/avto tial fo ek sp o b o ten ge) an ap o s)/ M p za n rarn zid h ed stru o 0 ig p raly altered h ačilen aleo o ltu ith steje ag riverb čen w ricu goo aleo ajp (p relief (p ast relief zn , n an stly ag area/izlo y terrain in o p p rb ravn a m ilt u d u : g at, m : raven at terrain : u u : b 1 : fl 2 : fl 3 b 1 D 2 D 3 D ed egen S E S E S E S R S R S R d /L A Z A Z A Z d L A L A L A xclu C R C R C R E egenL 29 Mateja Breg Valjavec, Detection of former landfills in gravel plain using geomorphometric analysis and High-Resolution LiDAR DTM v m ok 006 ad aljavec pd reg V IS 410 S S 0 2 0 ateja B 4 U Y IS Z IC L lagališče od a: M A S SC N je o R Y lls/ A ljevid an Z fi d L 0 H d N 0 M ek 2 IA C A lan / rica zem G ld A 4 . © E za n 9 N 4 r o m 9 9 1 9 y/avto T IC d A 1 cialo 0 b a a tial fo an in ap T 5 L 4 lik lik ten 8 M N 8 b b ten o 9 o E 9 p A, 1 a o IO a o p , 1 5 h im 57 7 ig M T k 9 IC 9 h O , 1 , 1 4 4 6 R a reliefn A a reliefn ith 6 9 9 w H čen , 1 , 1 9 O o IZ čeno P 9 5 5 9 T 9 /izb L b/v R ast relief z viso 1 y terrain in a rm p IS fo A rm d fo m yars 1 u M d U d : grb H : b 1 its in ice v letih 1 O egen lan D O S E zn S E vex IS /L cave lan R E o d n A Z o V no L A ravel p ram C G C C R G G g egenL 30 Acta geographica Slovenica, 54-1, 2014 flattened one (wavy, bumpy) with a multiresolution index of valley bottom flatness (MrVBF module in SAGA software) intended for charting the sedimentation areas (in this case paleo riverbeds). The MrVBF algorithm (Gallant and Dowling 2003) works on raster DTMs. The Valley Flatness (VF) at a single scale is calculated as a function of (1) the local topographic position of a cell within a moving window and (2) the slope of a 3 × 3 cell window. A cell is part of a flat valley when it is locally low and has a low slope. Fuzzy VF values for multiple resolutions are calculated by resampling the DEM to increasingly coarse solutions and then repeating the procedure (Gallant in Dowling, 2003). Using the two described geomorphometric indexes (Layer 1, Layer 2) the alluvial terrain of study area was classified in to three classes (Table 1 and Figure 5). Class 3 is representing paleo riverbeds (completely flat areas) the areas inside Class 2 correspond to agriculturally altered areas that express flat terrain, similar to natural characteristics while Class 1 cor- responds to areas of bumpy wavy terrain or terrain of landfills. The areas in Class 1 were named areas with a high terrain potential for landfills. 6 Disscusion and conclusions By overlapping results from visual analysis (from Figure 4) with results of geomorphometric analysis (from Figure 5) 26 of 46 visually detected potential landfills are matching with the CLASS 1(the areas of high terrain potential for landfill, grey polylines in Figure 6). These 26 objects can be relatively surely charac- terized as landfills (red polygons). To improve the reliability of results, obtained from LiDAR analysis, we compared them (Figure 6) with geo-historical data on known locations of old gravel pits (Breg Valjavec, Gostin~ar and Smrekar 2011). On the study area 30 gravel pits in different stage of excavation / degra- dation were registered from archive aerial photographs from years 1959, 1964, 1975, 1985 and 1994. Finally, only 8 locations were recognized with all three methods as the landfills. Huge quantity and density data, which is obtained by LiDAR, is still the best managed and present- ed by visualization technics (Kalawsky 2009 in: Mlekù 2010). Visualization technics are useful also at the local scale by studying smaller areas of flat landscapes. There are undoubtedly many options for determining landfills with the geomorphometric analysis of very precise LiDAR data in the future. The success in detec- tion of landfills with geomorphometric analysis depends very much on the type of landfills, their micro-terrain characteristics and land use type above buried waste. The applied geomorphometric analy- sis is the suitable way for detection of convex and slightly convex bumpy objects that are potential landfills. On Figure 6 are represented as red polylines overlapping grey and grey-blue dashed areas. Concave and slightly concave landforms (on Figure 6 are represented as black polylines overlapping white areas) are converging areas representing either concave anthropogenic landforms (partially filled gravel pits, pre- served gravel pits) or concave natural landforms and must be additionally studied with field survey in order to detect buried waste. The method enables the best results on areas of agrarian land use (fields, intensive meadows) as well on open surfaces with no significant higher vegetation cover (no tress). In contrary, the methodology is almost not applicable for overgrowing areas inside agrarian land use and in forest as they express similar micro-terrain characteristics as waste pits. In order to improve results and to distinguish between natural and anthropogenic terrain in those land use types it is needed to study the vegetation cover (tree density and height). In addition some analysis of the ortho-photo images (i.e., infrared band) in combination with LiDAR vegetation layer can be performed. Regarding the field work on known landfills (Breg Valjavec 2012) we can assume that if the trees are tall and dense, it means they flourish on a stable natural rock founda- tion and natural soils that enable a stable growth to higher plants. Lower trees of bush growth inside forest may flourish on the areas of filled gravel pits, as the anthropogenic soils (deposols) and the inhomogeneous original foundation (waste) does not guarantee a static stability to the tall trees (e.g. English oak). With future research the applied methodology should be improved in the framework of existing geo- morphometric methods using GIS terrain modeling and additional data layers (land use data and near-infrared aerial photographs) as well as with more object oriented geomorphometric analysis. The presented geomorphometric analysis individually enables only detection of broader areas having ter- rain characteristics similar to landfills but not exactly the individual landfills object. Regarding the geomorphological backgrounds, on which the object oriented concept is based, the methodology could be applied in studying landfills in similar alluvial plains along rivers and can be put into the context of paleo riverbeds on floodplains. 31 Mateja Breg Valjavec, Detection of former landfills in gravel plain using geomorphometric analysis and High-Resolution LiDAR DTM 7 References Anders, N., S., Seijmonsbergen, A., C., Bouten, W., 2009: Multi-scale and object-oriented image analysis of high-res LiDAR data for geomorphological mapping in Alpine Mountains. Proceedings of gemor- phometry 2009. Zurich. Breg, M., Urbanc, M., 2005: Gravel plains in urban areas: gravel pits as an element of degraded landscapes. Acta geographica Slovenica 45-2. DOI: http://dx.doi.org/10.3986/AGS45202 Breg, M., Urbanc, M., 2009: Skrite in odkrite gramoznice na Jar{kem produ – odpadkovnice? Geografski obzornik 56-3. Breg M., Kladnik D., Smrekar A., 2007: Dumping sites in the Ljubljansko polje water protection area, the pri- mary source of Ljubljana's drinking water. Acta geographica Slovenica 47-1. DOI: http://dx.doi.org/ 10.3986/AGS47104 Breg Valjavec, M., 2010: Digitalni model vi{in nekdanje pokrajine – primer Loga{ko polje (leto 1972). Geografski informacijski sistemi v Sloveniji 2009–2010. Ljubljana. Breg Valjavec, M., 2012: Geoinformatic methods for the detection of former waste disposal sites in karstic and nonkarstic regions (case study of dolines and gravelpits). Doctoral thesis, University of Nova Gorica, Graduate school. Internet: http://www.ung.si/~library/doktorati/krasoslovje/10BregValjavec.pdf (15. 10. 2014). Breg Valjavec, M., Gostin~ar, P., Smrekar, A. 2012: Register virov onesnaèvanja vodonosnikov Ljubljanskega polja in Barja. Geografski informacijski sistemi v Sloveniji 20011–2012. Ljubljana. Bricelj, M., 1988: Popis odlagali{~ odpadkov in pokrajinsko-ekolo{ki vidiki izbora alternativnih lokacij za urejeno odlaganje smeti v ob~ini Logatec. Ljubljana. Bujána, S., González-Ferreiroa, E., Barreiro-Fernándeza, L., Santéa, I., Corbellea, E., Mirandaa, D., 2013: Classification of rural landscapes from low-density lidar data: is it theoretically possible? International journal of remote sensing 34-16. DOI: http://dx.doi.org/10.1080/01431161.2013.792230 Cigli~, R., Gostin~ar, P., 2011: Primerjava rezultatov ra~unalni{kega prepoznavanja reliefnih oblik z rezul- tati geomorfolo{kega kartiranja. Geografski vestnik 83-1. Gallant, J. C., Dowling, T. I., 2003: A multiresolution index of valley bottom flatness for mapping depo- sitional areas. Water resources research 39. DOI: http://dx.doi.org/10.1029/2002WR001426 Geoin d. o. o. Geodetski inèniring Maribor, 2011: Laserski posnetek obmo~ja Kle~e. Ghanavati, E., Firouzabadi, P. Z., Jangi, A. A., Khosravi, S., 2008: Monitoring geomorphologic changes using Landsat TM and ETM+ data in the Hendijan River delta, southwest Iran. International journal of remote sensing 29, 3-4. DOI: http://dx.doi.org/10.1080/01431160701294679 Hengl, T., Reuter, H. I. 2009: Geomorphometry: concepts, software, applications. Amsterdam. Hrvatin, M., Perko, D. 2009: Suitability of Hammond's method for determining landform units in Slovenia. Acta geographica Slovenica 49-2. DOI: http://dx.doi.org/10.3986/AGS49204 Komac, B. 2009: Social memory and geographical memory of natural disasters. Acta geographica Slovenica 49-1. DOI: http://dx.doi.org/10.3986/AGS51101. Ku{ar, S., 2001: Metodologija ocenjevanja pokrajinskega vpliva neurejenih odlagali{~ odpadkov na kakovost podtalnice v prodnih sedimentih. Geografski vestnik 73-1. Lidar 2008, © GEOIN/Geodetski inèniring, Maribor. Mlekù, D., 2010: Lidar in geoarheologija aluvialnih pokrajin. Geografski informacijski sistemi v Sloveniji 2009–2010. Ljubljana. Pacina, J., Weiss, L., 2011: Georelief reconstruction and analysis based on historical maps and aerial photographs. Symposium GIS Ostrava proceedings. Ostrava. Podobnikar, T., Moìna, P., 2008: Analiza oblik povr{ja z uporabo lokalnega okna. Geografski informa- cijski sistemi v Sloveniji 2007–2008. Ljubljana. Podobnikar, T., Schöner, M., Jansa, J., Pfeifer, N. 2008: Spatial analysis of anthropogenic impact on karst geomorphology (Slovenia). Environmental geology 58-2. DOI: http:/ dx.doi.org/10.1007/s00254-008-1607-3 Radinja, D. 1951: Sava na Ljubljanskem polju. Geografski vestnik 23. Silvestri, S., Omri, M., 2008: A method for remote sensing identification of uncontroled landfills: formulation and validation. International Journal of Remote Sensing 29, 3-4. DOI: http://dx.doi.org/10.1080/01431160701311317 Smrekar, A., 2007: Divja odlagali{~a odpadkov na obmo~ju Ljubljane. Georitem 1. Ljubljana. 32 Acta geographica Slovenica, 54-1, 2014 [ebenik I., 1994: Pokrajinske zna~ilnosti manj{ih neurejenih odlagali{~ odpadkov v Sloveniji. Geographica Slovenica 26-1. [ifrer, M. 1969: Kvartarni razvoj Dobrav na Gorenjskem. Acta geographica 11. Yoëli, P.,1965: Analytische Schattierung. Ein kartographischer Entwurf. Kartographische Nachrichten 15-5. Zak{ek, K., Kokalj, @., O{tir, K., 2010: Uporaba deleà vidnega neba za vizualizacijo reliefa. Geografski infor- macijski sistemi v Sloveniji 2009–2010. Ljubljana. 33 Mateja Breg Valjavec, Od kri va nje pri kri tih odla ga li{~ odpad kov v prod ni rav ni ni z geo mor fo me tri~ no ana li zo in LiDAR DMR Od kri va nje pri kri tih odla ga li{~ odpad kov v prod ni rav ni ni z geo mor fo me tri~ no ana li zo in LiDAR DMR DOI: http://dx.doi.org/10.3986/AGS54106 UDK: 911.2:551.43(497.451Lj. polje) 551.43:628.472.3(497.451Lj. polje) 628.472.3:528.8(497.451Lj. polje) COBISS: 1.01 IZVLE^EK: V ~lan ku pred stav lja mo geo mor fo lo{ ki pri stop za odkri va nje nek da njih odla ga li{~ odpadkov v prod ni rav ni ni na pri me ru Ljub ljan ske ga polja. Ve~i na nek da njih odla ga li{~ odpad kov je skri tih v vbo - ~e nih relief nih obli kah: sta rih neak tiv nih gra moz ni cah ali sta rih re~ nih stru gah (pa leo stru ge). Z vi zual no inter pre ta ci jo relie fa smo naj prej dolo ~i li antro po ge ne relief ne obli ke, ki so nasta le zara di izko pa va nja proda in relief ne obli ke, ki se izob li ku je jo z od la ga njem odpad kov v ko ta nje. Upo ra bi li smo LiDAR DMR, ki smo ga pri ka za li s po mo~ jo ana li ti~ ne ga sen ~e nja in hip so me tri~ ne barv ne les tvi ce. Ugo to vi li smo, da je zaradi pose da nja hete ro ge nih odpad kov, relief nek da njih odla ga li{~ v ko ta njah, ki niso bila stro kov no sanira na, grbi nast in zato nez na ~i len za linij sko obli ko van flu vial ni relief prod ne rav ni ne. Na pod la gi teh ugo to vi - tev vizual ne ana li ze, smo s po mo~ jo dveh geo mor fo me tri~ nih indek sov (kon ver gen~ ni indeks in indeks plo sko sti) flu vial ni relief prod ne rav ni ne lo~i li v tri raz re de: (1) grbi na sti relief, zna ~i len za poten cial na pri kri ta odla ga li{ ~a, (2) rav ni relief zna ~i len za dna sta rih strug ter (3) »agrar ni« relief, zna ~i len za inten - ziv no obde la na kme tij ska zem lji{ ~a. S pri mer ja vo rezul ta tov obeh metod smo 26 od 46 an tro po ge nih relief nih oblik, ki smo jih dolo ~i li z vi zual no ana li zo, potr di li tudi z geo mor fo me tri~ no ana li zo. Le 8 od teh 26 ob - jek tov pa se uje ma tudi z nek da nji mi gra moz ni ca mi, dolo ~e ni mi na arhiv skih aero po snet kih. KLJU^NE BESEDE: upo rab na geo gra fi ja, odla ga li{ ~e odpad kov, gra moz ni ca, sta ra stru ga, vizual na inter - pre ta ci ja, tek stu ra, geo mor fo me tri ja, LiDAR, DMR, Ljub ljan sko polje. Ured ni{ tvo je pre je lo pris pe vek 14. ja nuar ja 2013. NASLOV: Dr. Mate ja Breg Valja vec Geo graf ski in{ti tut Anto na Meli ka Znans tve no ra zi sko val ni cen ter Slo ven ske aka de mi je zna no sti in umet no sti Novi trg 2, SI – 1000 Ljub lja na, Slo ve ni ja E-po {ta: mate ja.bregazrc-sazu.si 34 Acta geographica Slovenica, 54-1, 2014 1 Uvod Glav na razi sko val na tema so nek da nja odla ga li{ ~a odpad kov v ko ta njah Ljub ljan ske ga polja. To so podzem - ni objek ti, za kate re je zna ~il na nepoz na na in hete ro ge na struk tu ra sta rih odpad kov, s ka te ri mi so zapol nje ne vbo ~e ne relief ne obli ke. Rezul ta ti pred hod nih doma ~ih {tu dij (Bri celj 1988; [ebe nik 1994; Ku{ar 2001; Breg in Urbanc 2005, Breg s so de lav ci 2007; Smre kar 2007 itd.) in pri mer lji vih med na rod nih {tu dij (Sil - ve stri in Omri 2008) doka zu je jo, da je bilo odla ga nje odpad kov v pre te klo sti veza no ve~i no ma na narav ne (sta re stru ge, vrta ~e) in antro po ge ne kota nje (gra moz ni ce). Sklad no s tem bomo v ra zi ska vi pred sta vi li relief ne zna ~il no sti z od pad ki zapol nje nih kotanj (gra moz ni ce in sta re struge) ter mò no sti za dolo ~a nje le-teh na pod la gi geo mor fo lo{ kih zna ~il no sti. Glav ni cilj razi ska ve je daljin sko zaz na va nje nek da njih odla ga li{~ odpad kov, skri tih pod povr{ jem, s po - mo~ jo ana li ze LiDAR podat kov, ki teme lji na geo mor fo lo{ kih meto dah in poz na va nju geo mor fo lo gi je obre~ ne prod ne pokra ji ne. Kljub izjem ni natan~ no sti in upo rab no sti LiDAR podat kov pa lah ko na LiDAR DMR dolo ~a mo samo pod zem na odla ga li{ ~a, kate rih posle di ce so vid ne na zemelj skem povr{ ju in zato na DMR. To velja za odla ga li{ ~a, ki niso bila pre kri ta (sa ni ra na) z us trez no debe lo plast jo rodo vit ne zemlji - ne, ki bi omo go ~a la inten ziv no kme tij sko obde la vo. Na tovrst nih odla ga li{ ~ih zato ni pri sot na inten ziv na kme tij ska raba tal ampak traj ni trav ni ki in zara{ ~a nje, kar se odra à v mi kro-re lie fu ozi ro ma tek stu ri pri - ka za ne ga relie fa. V pre te klih {tu di jah so posku {a li zaz na va ti pod zem na odla ga li{ ~a z upo ra bo raz li~ nih teh nik daljin - ske ga zaz na va nja pred vsem z upo ra bo ve~-spek tral nih sate lit skih posnet kov. Pou da rek je bil na zaz na va nju degra di ra nih tal, s pou dar kom na degra di ra nem rast lins tvu in prsti. Podrob nej {i pre gled daljin ske ga zazna - va nja raz li~ nih tipov odla ga li{~ odpad kov je na voljo v ~lan kih Sil ve stri ja in Omri ja (2008) ter Slo nec ker ja s so de lav ci (2010). Bis tve no manj razi skav je bilo nare je nih z vi di ka preu ~e va nja relief nih posle dic, ki nasta - ne jo zara di odla ga nja odpad kov. V ta namen so bili upo rab lje ni sate lit ski posnet ki raz li~ nih pro stor skih in spek tral nih lo~ lji vo sti (Land sat TM, Land sat ETM, Quick bird, Iko nos, Geo Eye1), kjer so z vi zual no analizo dolo ~a li geo mor fo lo{ ke spre mem be, kot je dina mi ka pre stav lja nja re~ nih strug, spre mi nja nje mor ske oba - le, mean drov in rekon struk ci ja sta rih re~ nih strug (Gha na va ti s so de lav ci 2008). Podob ni kar s so delav ci (2008) ugo tav lja, da ana li za DMR s 25 m lo~ lji vost jo celi ce omo go ~a tudi preu ~e va nje ve~ jih geo mor fo lo{ kih spre - memb, ki jih je pov zro ~il ~lo vek: cest ni nasi pi, pro met na, infra struk tu ra, zasu te vrta ~e, aktiv ne gra moz ni ce. Pose ben pri stop dolo ~a nja antro po ge nih relief nih spre memb je tudi dolo ~a nje volu me tri~ nih spre memb relie fa, ki jih kvan ti ta tiv no dolo ~a mo z is ka njem raz lik med DMR-ji iste ga obmo~ ja iz raz li~ nih obdo bij. S fo to gra me tri~ no meto do ste reo-iz vred no te nja arhiv skih aero po snet kov lah ko pri ka è mo relief v nek - da nji pokra ji ni. Relief nek da nje pokra ji ne pri mer ja mo z re lie fom dana{ nje pokra ji ne in na tak na~in dolo ~i mo vi{in ske raz li ke in na pri mer zasu te kota nje. Tovr sten na~in je bil upo rab ljen za dolo ~a nje zasu tih vrta~ na Loga{ kem polju (Breg Valja vec 2010) ter v pri me ru povr {in ske ga kopa rud ni ka Bili na (Slo va{ ka), kjer so na podo ben na~in z vo lu me tri~ no ana li zo dolo ~i li koli ~i no izko pa ne rud ni ne v do lo ~e nem obdob ju (Pa ci na in Weiss 2011). Ker so odla ga li{ ~a, ki zapol nju je jo gra moz ni ce, {te vil na in po alu vial ni pokra ji ni zelo raz pr {e na, je geo - mor fo me tri~ na ana li za relie fa pri kri tih odla ga li{~ usmer je na v re lief ne zna ~il no sti manj {ih lokal nih obmo ~ij. Z do stop nost jo viso ko lo~ lji vih LiDAR podat kov, raz vo jem digi tal nih geo mor fo me tri~ nih metod in poseb - ne pro gram ske opre me je posta lo mò no tudi odkri va nje pri kri tih odla ga li{~ z raz poz na va njem (mi kro) relief nih posle dic. DMR, ki je izde lan iz laser ske ga obla ka to~k, omo go ~a dolo ~a nje naj manj {ih raz lik v topo - gra fi ji (od nekaj cen ti me trov do nekaj deset cen ti me trov), ki so posle di ca geo mor fo lo{ kih ali antro po ge nih pro ce sov. LiDAR omo go ~a opa zo va nje sle dov ~lo ve{ ke ga delo va nja iz raz li~ nih ~asov nih obdo bij (pla sti pokra ji ne), z njim raz poz na va mo braz go ti ne in prst ne odti se narav nih in antro po ge nih pro ce sov na povr{ini Zem lje (Ko mac 2009; Mle kù 2010) ter odkri va mo tek stu ro »braz go tin«, ki so bile ustvar je ne v na ravnem relie fu zara di pod zem ne ga odla ga nja odpad kov. 2 Preu ~e va no obmo~ je Ljub ljan sko polje je tek ton ska udo ri na zapol nje na pred vsem s prod ni mi in pe{ ~e ni mi sedi men ti. V fluvial - nem relie fu ob reki Savi so izob li ko va ne {te vil ne tera se, vi{ ja plei sto cen ska in nì je holo cen ske (Ra di nja 1951; [ifrer 1969). S pre stav lja njem re~ ne ga toka iz sta rih v novo nasta ja jo ~e stru ge so pred vsem na holo censkih 35 Mateja Breg Valjavec, Od kri va nje pri kri tih odla ga li{~ odpad kov v prod ni rav ni ni z geo mor fo me tri~ no ana li zo in LiDAR DMR tera sah ohra nje ne sta re opu{ ~e ne stru ge. V po kra ji ni jih lah ko opa zu je mo kot podol go va te rah lo vbo ~ene relief ne obli ke, {e pose bej v nì jih holo cen skih tera sah. [tu dij sko obmo~ je (sli ka 4) pred stav lja obmest no obmo~ je na sever nem robu mesta Ljub lja ne s pre - vla du jo ~o kme tij sko rabo tal (trav ni ki in nji ve), ki pre ha ja v mla do gozd no vege ta ci jo na pro di{ ~ih ob reki Savi. Obmo~ je je v ne po sred ni bli ì ni mesta, zato je zanj zna ~il no, da je pod vpli vom neza ko ni te ga odla - ga nja odpad kov (Breg in Urbanc 2005). Zara di prod na tih sedi men tov, je Ljub ljan sko polje è od nek daj zani mi vo za pri do bi va nje gra mo za, zla sti v bli ì ni reke Save. Mno ge sred nje veli ke gra moz ni ce (od 1000 do 5000 m2), so bile v pre te klo sti del no ali v ce lo ti zapol nje ne z od pad ki in so se spre me ni le v »od pad kov ni - ce« (Breg in Urbanc 2009). 3 Meto do lo gi ja in LiDAR podat ki S preu ~e va njem osnov nih geo mor fo lo{ kih zna ~il no sti narav ne ga relie fa prod ne rav ni ne in dolo ~a njem zna ~il no sti antro po ge nih relief nih oblik smo posta vi li geo mor fo lo{ ki pri stop za odkri va nje pod zem no odlo - è nih odpad kov in s tem nek da njih odla ga li{~ odpad kov. Upo rab ljen geo mor fo lo{ ki pri stop, vklju ~u je dva na~i na iska nja in preu ~e va nja pod zem nih odla ga li{~ na DMR: (1) vizual na inter pre ta ci ja relie fa in (2) geo mor fo me tri~ na ana li za. Pri tem smo upo {te va li dejs tvo, da z upo ra bo in pri mer ja vo ve~ metod dose - è mo ve~ jo stop njo natan~ no sti dolo ~i tve relief ne obli ke (Ci gli~ in Gostin ~ar 2011). Nume ri~ na, v tem pri me ru geo mor fo me tri~ na ana li za, kot tudi vizual na ana li za DMR omo go ~a ta dolo ~a nje narav nih reliefnih oblik in tudi antro po ge nih relief nih oblik (Po dob ni kar in Moì na 2008). Loka ci je in relief ne zna ~il no sti z od pad ki zapol nje nih kotanj smo naj prej dolo ~i li z me to da mi vizual ne inter pre ta ci je relie fa v na da ljeva - nju pa z geo mor fo me tri~ no ana li zo in kla si fi ka ci jo flu vial ne ga relie fa. Upo ra bi li smo LiDAR DMR (Li dar 2008 © GEOIN) izde lan na pod la gi laser ske ga ske ni ra nja povr{ ja z dne 8. in 14. fe bruar ja 2008. Sne ma nje je pote ka lo z Op tech Gemi ni LiDAR sen zor jem. Pri mar na obde la va podat kov je bila oprav lje na z Dash map 5.3 in pro gram sko opre mo Pos Pac 4.4. Za kla si fi ka ci jo in obde la vo podat kov je bil upo rab ljen pro gram ski paket Ter ra Solid in Micro sta tion (Ge oin 2011). Izmed {ti rih raz re dov kla si fi ci ra ne ga oblaka to~k, smo upo ra bi li sloj relief, ki smo ga s pred hod ni mi obde la va mi zgla di li. Iz ana li ze so bila izklju ~e na pozi da na obmo~ ja, ker na njih ni mò no dolo ~a ti nek da njih odla ga li{~. 4 Vizual na inter pre ta ci ja in zna ~il no sti antro po ge ne ga relie fa odla ga li{~ Re lief ne ano ma li je, ki so pred vi do ma antro po ge ne ga nastan ka, smo dolo ~a li na LiDAR DMR, ki smo ga pri ka za li z raz li~ ni mi teh ni ka mi vizua li za ci je. Ne gle de na {irok spek ter upo ra be DMR, je prva stop nja nje go ve upo ra be nazo ren pri kaz ozi ro ma vizua li za ci ja nume ri~ nih podat kov o nad mor skih vi{i nah. Kljub mno gim opi som napred nih pri ka zov relie fa, osta ja ana li ti~ no sen ~e nje ena naj po go stej {ih metod (Zak{ek s so de lav ci 2010). Ana li ti~ no sen ~e nje (Sli ka 2 in 3) pome ni le ra~u nal ni{ ko pod pr to izde la vo sen ~e ne ga relie fa iz DMR. Kot stan dard se je uve lja vi la meto da, ki jo je raz vil Yoëli (1965) in pri kate ri je vred nost sivi ne soraz mer na kosi nu su vpad ne ga kota àr ka nepo sred ne osvet li tve relie fa. Gre za kot med smer jo pro ti viru svet lo be in pra vo kot ni co na plo skev relie fa. Tako so obmo~ ja pra vo kot na gle de na àrek iz navi dez - ne ga svet lob ne ga vira bela, obmo~ ja z vpad nim kotom osvet li tve 90° ali ve~, pa so v po pol ni sen ci in so ~rna, med tem ko so obmo~ ja z vpad nim kotom med 0° in 90° pri ka za na z us trez nim sivim ali dru gim barv nim tonom (Zak {ek s so de lav ci 2010). Hip so me tri ja (Sli ka 1) je vizua li za cij ska teh ni ka, kjer pri ka - è mo vred no sti DMR s hip so me tri~ no barv no les tvi co. Z raz te za njem ali kr~e njem histo gra ma sli ke pri la go di mo pri kaz potre bam ana li ze. V na {em pri me ru je to izpo stav lja nje manj {ih relief nih oblik ozi - ro ma zna ~il no sti mikro-re lie fa. Obe vizua li za cij ski teh ni ki, ana li ti~ no sen ~e nje in hip so me tri ja, smo upo ra bi li na manj {ih izse kih podat kov LiDAR (ve li kost 750 m × 500 m) s ~i mer smo zmanj {a li inter val med najnì - jo in naj vi{ jo vred nost jo sli ke (nad mor sko vi{i no) ter dose gli bolj {i barv ni kon trast v pri ka zu relie fa rav ni ne in izra zi tej {o osen ~e nje mikro-ob lik (Sli ka 1, levo). S tak {no meto do lo gi jo pri ka za DMR smo zelo natan~ - no rekon strui ra li potek sta rih strug v agrar ni pokra ji ni. Dolo ~i li smo zna ~il no sti flu vial ne ga relie fa prod ne rav ni ne (suhe stru ge) in geo mor fo lo{ ko izob li ko va nost obmo ~ij z od pad ki zapol nje nih kotanj. Za nadalj - njo geo mor fo me tri~ no ana li zo je bis tve na zna ~il nost sta rih strug. Ima jo obsè no lon gi tu di nal no ravno 36 Acta geographica Slovenica, 54-1, 2014 dno (na klon pod 0,5°) in hiter porast naklo na v bre ì nah, kar omo go ~a tudi natan~ no geo mor fo me tri~no opre de li tev sta rih re~ nih strug. Z vi zual no inter pre ta ci jo smo odkri li izbo ~e ne ano ma li je v stru gah, ki so posle di ca antro po ge nih aktiv no sti in s tem poten cial na odla ga li{ ~a odpad kov. Pre ki ni tve strug se poja vi - jo lokal no, kjer na dolo ~e nem odse ku stru go pre ki ne izbo ~e na obli ka (kup odpad kov), stru ga pa se po pre ki ni tvi nada lju je (Sli ka 1). Kako vost vizual ne inter pre ta ci je izbo ~e nih antro po ge nih relief nih oblik zno - traj sta rih strug na LiDAR DMR je odvi sna od veli ko sti vizua li zi ra ne ga obmo~ ja DMR. Na levi sli ki je pove ~an pogled iz DMR veli ko sti 750 × 500 m in na desni sli ki pove ~an pogled v DMR celot ne ga obmo~ ja. Sli ka 1: Rekon strui ra nje sta rih strug z vi zual no ana li zo na raz li~ no veli kih izse kih DMR in relief ne ano ma li je v stru gi. Glej angle{ ki del pris pev ka. Z od pad ki zasu te gra moz ni ce v flu vial nem relie fu rav ni ne ne izsto pa jo izra zi to, saj so bile z za sut jem izrav na ne z oko li{ kim relie fom. Ker so odpad ki zelo hete ro ge ni, raz pa da jo z raz li~ no inten ziv nost jo in se tudi raz li~ no pose da jo. Grbi nast relief, ki se v de set let jih obli ku je nad odpad ki, se raz li ku je od flu vial nega relie - fa v prod na ti oko li ci (sli ka 2). @e latin sko ime (lat. Flu vio pome ni reko) pove, da so flu vial ne reliefne obli ke nasta le zara di toka vode. [ir {e gle da no obli ku je flu vial ni relief celot na hidro graf ska mre à, kjer se lami - nar ni toko vi zdru ù je jo v li near ne ga in na kon cu v reko. Narav ne flu vial ne obli ke so, zara di tak {ne ga delovanja vode, linear nih oblik (do li na, gra pa, sote ska, ero zij ski jarek, sle me), med tem ko so grbi na ste relief ne oblike, zna ~il ne za z od pad ki zapol nje ne gra moz ni ce, neli near ne. Naj bo lje jih zaz na mo z vi zual no inter pre ta cijo sen ~e ne ga relie fa (Sli ka 2). Narav ni flu vial ni relief preu ~e va ne pokra ji ne je mo~ no preob li ko van pred vsem zara di tra di cio nal ne in inten ziv ne kme tij ske rabe tal. Na viso ko-lo~ lji vih LiDAR DMR-jih lah ko u~in ke raz li~ ne rabe tal zaz na mo in omo go ~a jo kla si fi ka ci jo raz li~ nih tipov rabe tal. V pri me ru z od pad ki zapolnjenih kotanj ima jo pomemb no vlo go raz li~ no pose da jo ~i se odpad ki, ki pred stav lja jo antro po geno mati~ no podlago. Na pod la gi vizual ne ana li ze relie fa ugo tav lja mo tudi, da pri izob li ko va nju mikro-re lief nih oblik v po - vsem rav nem flu vial nem relie fu pogo sto prev za me jo vodil no vlo go (pre)ob li ko va nja relie fa pokra jin ske prvi ne kot je mati~ na pod la ga (tudi antro po ge na na pri mer odpad ki), prst (glo bi na prsti), rast lins tvo (dre - ve sne kore ni ne), ìvals tvo (de lo va nje krta) in navse zad nje ~lo vek (ora nje). Sklad no s tem smo odla ga li{ ~em podo ben grbi nast relief odkri li tudi v ti pih rabe tal, kjer ni antro po ge nih vpli vov: • grbi nast mikro-re lief relief na pogoz de nih pro di{ ~ih ob Savi, ki se izob li ku je zara di de lo va nja kore nin in zar di pli tve rend zi ne; • grbi nast mikro-re lief je zna ~i len za opu{ ~e ne kme tij ske povr {i ne, zno traj inten ziv nih kme tij skih zem - lji{~ in je ome jen na manj {e paso ve (na pri mer meji ce) ali par ce le; • grbi nast mikro-re lief na pa{ni ku ali traj nem trav ni ku, kjer so pri sot na dre ve sa (ze le ni obro~ na Sli ki 3). Do kon~ no raz lo ~e va nje med opi sa ni mi narav ni mi grbi na sti mi mikro-re lief ni mi obli ka mi ter antro - po ge ni mi grbi na sti mi obli ka mi, ki nasta ne jo na z od pad ki zapol nje nih kota njah, je mò no z geo-hi sto ri~ no ana li zo in dolo ~i tvi jo gra moz nic v pre te klo sti (ana li za arhiv skih letal skih posnet kov), rekon struk ci jo sta - rih strug in teren skim vzor ~e njem (npr, prsti). Sli ka 2: Relief z od pad ki zapol nje ne in samo zatrav lje ne gra moz ni ce je naj po go ste je rah lo grbi nast. Relief oko li{ kih njiv pa je spre me njen zara di ora nja in rah lja nja prsti. Glej angle{ ki del pris pev ka. Sli ka 3: Izob li ko va nost povr{ ja na traj nem trav ni ku (ob mo~ je ome je no z ze le no) je zelo podob no izob li ko va no sti povr{ ja na z od pad ki zapolnjeni zatrav lje ni gra moz ni ci (glej sli ko 2). Glej angle{ ki del pris pev ka. Na vzor~ nem obmo~ ju (ve li kem 5 km2) smo z vi zual no ana li zo DMR dolo ~i li 67 an tro po ge nih reliefnih oblik, ki se nave zu je jo na izko pa va nje gra mo za (gra moz ni ce) in odla ga nje odpad kov (Sli ka 4). Antro poge - ne relief ne obli ke smo raz de li li v {ti ri sku pi ne gle de na vbo ~e nost / izbo ~e nost ter raz gi ba nost relie fa (gr bi nast relief) (Sli ka 4): 1. Izbo ~e ne relief ne obli ke, so poten cial na odla ga li{ ~a odpad kov, ki so nasta la v pre na pol nje ni gra moznici ozi ro ma pred stav lja jo kup odpad kov dvig njen nad raven oko li{ ke ga povr{ ja. 2. Grbi na ste relief ne obli ke (po ten cial na odla ga li{ ~a): 2A. grbi nast (rah lo) izbo ~en mikro-re lief, 2B. grbi nast (rah lo) vbo ~en mikro-re lief, 3. Vbo ~e ne relief ne obli ke so dom nev no opu{ ~e ne gra moz ni ce ali narav ne sta re stru ge; 37 Mateja Breg Valjavec, Od kri va nje pri kri tih odla ga li{~ odpad kov v prod ni rav ni ni z geo mor fo me tri~ no ana li zo in LiDAR DMR Pri izbo ~e nih (5), grbi na stih rah lo izbo ~e nih (24) in grbi na stih rah lo vbo ~e nih (17) obli kah relie fa je sum, da so nasta le zara di odla ga nja odpad kov v ko ta nje, naj ve~ ji, zato so nji ho ve zna ~il no sti pomemb ne kot osno va za nadalj njo geo mor fo me tri~ no ana li zo. Sklad no s tem je rezul tat vizual ne ana li ze 46 po ten - cial nih odla ga li{~ odpad kov v ko ta njah. Sli ka 4: Pro stor ska raz po re di tev antro po ge nih relief nih oblik, ki smo jih dolo ~i li z vi zual no ana li zo LiDAR DMR na preu ~e va nem obmo~ ju Ljub ljan ske ga polja. Glej angle{ ki del pris pev ka. 5 Geo mor fo me tri~ na ana li za in rezul ta ti Geo mor fo me tri ja je veda, ki se ukvar ja s kvan ti ta tiv nim preu ~e va njem relie fa; njen cilj je pri do bi va nje relief nih para me trov in relief nih oblik na pod la gi digi tal nih mode lov relie fa (Hengl in Reu ter 2009, Hrvatin in Per ko 2009). Sodob na geo mor fo me tri ja se raz li ku je od kla si~ ne kvan ti ta tiv ne geo mor fo lo gi je po tem, da teme lji povsem na ra~u nal ni{ ki ana li zi relie fa (Hengl in Reu ter 2009). Geo mor fo me tri~ na ana li za je dru - ga stop nja na{e razi ska ve, s ka te ro èli mo avto mat sko dolo ~i ti obmo~ ja, ki ima jo relief ne zna ~il no sti z od pad ki zasu tih kotanj. Di gi tal ni model relie fa lah ko raz de li mo v raz re de z upo ra bo geo mor fo me tri~ nih para me trov kot je naklon in ukriv lje nost relie fa. Za natan~ nej {o kla si fi ka ci jo geo mor fo lo{ kih oblik upo ra bi mo dodat ne para - me tre, kot je na pri mer aku mu la ci ja vod ne ga toka za dolo ~a nje relief nih oblik pove za nih s flu vial ni mi pro ce si (An ders s so de lav ci 2009). Z izra ~u nom kon ver gen~ ne ga indek sa relie fa ( In dex of con ver gen ce) smo izlo ~i li urav na na kon ver gent na obmo~ ja, saj niso zna ~il na za è pred stav lje ni relief z od pad ki zasutih kotanj pa~ pa ozna ~u je jo narav ne vbo ~e ne relief ne obli ke (sta re stru ge) in neza su te gra moz ni ce. Modul je vgra jen v pro gram SAGA in izra ~u na va indeks povr {in ske ga ste ka nja / raz te ka nja vode. Po pome nu je podo ben pla nar ni ali hori zon tal ni ukriv lje no sti relie fa ( cur va tu re), a daje veli ko bolj {e rezul ta te. Izra ~un teme lji na celi cah v oko li ci, t. j. preu ~i, do kate re sto pi nje celi ce v oko li ci so usmer je ne na sre din sko celico. Rezul tat je pred stav ljen v od stot kih, kjer nega tiv ne vred no sti ustre za jo ste ka nju, pozi tiv ne vred no sti pa odte - ka nju vod ne ga toka. Obmo~ ja rav ne ga relie fa smo od nerav ne ga (va lo vi te ga, grba ste ga) lo~i li z in dek som plo sko sti relie fa (ang. mul ti re so lu tion index of val ley bot tom fla te ness – MrVBF). Sled nji se izra ~u na s sa - mo stoj nim modu lom v pro gra mu SAGA, name njen pa je kar ti ra nju sedi men ta cij skih obmo ~ij (v na {em pri me ru sta re stru ge). Algo ri tem za izra ~un indek sa plo sko sti (Gal lant in Dow ling, 2003) delu je, kot kon - ver gen~ ni indeks, na rastr skih DMR. Plo skost doli ne (ang. val ley bot tom fla te ness, VF) je izra ~u na na kot funk ci ja lokal ne topo graf ske lege v ce li ci zno traj pre mi ka jo ~e se sen ce in pobo~ ja v 3 × 3 oknu celi ce. Celi - ca je del rav ne doli ne, ki je lokal no plo ska in ima niz ko pobo~ je. Prib lì ne vred no sti za ve~ lo~ lji vo sti so izra ~u na ne tako, da ponov no vzor ~i mo DMR na ved no bolj sla be lo~ lji vo sti in pri tem ponav lja mo posto - pek. Indeks plo sko sti je tako izmer je na kom bi na ci ja posa mez nih vred no sti VF, kjer so vred no sti VF, ki so manj {e od 0,5, dolo ~e ne kot gre be ni in so zato izlo ~e ne (Gal lant in Dow ling 2003). Na pod la gi rezul ta tov opi sa nih geo mor fo me tri~ nih indek sov (sloj 1, sloj 2) smo relief alu vial ne rav - ni ne raz de li li v tri raz re de (pre gled ni ca 1, sli ka 5). Raz red 3 pred stav lja relief zna ~i len za dna sta rih suhih strug (po vsem raven relief). V raz red 2 spa da antro po ge no spre me njen raven agrar ni relief, ki je posle - di ca kme tij ske ga obde lo va nja in je zna ~i len za nji ve in inten ziv ne trav ni ke. Za raz red 1 je zna ~i len grbi nast, rah lo valo vit relief, ki se pojav lja na odla ga li{ ~ih odpad kov a tudi na povsem narav nih obmo~ jih kot je Pre gled ni ca 1: Posto pek zdru è va nja rezul ta tov obeh geo mor fo me tri~ nih indek sov. sloj ime slo ja vred nost celi ce vred nost celi ce Sloj 1 + 2 sloj 1 kon ver gen~ ni 0 (ob mo~ je ste ka nja 1 (ob mo~ je raz te ka nja indeks vode – vbo ~en relief) vode – izbo ~en relief) sloj 2 in deks plo sko sti 0 (ra ven relief) 1 (ne ra ven, RAZRED 2 grbi nast relief) 1 (urav nan antro po ge no RAZRED 3 RAZRED 1 spre me njen relief) sloj 1 + 2 0 (sta ra stru ga) 2 (gr bi nast relief) 38 Acta geographica Slovenica, 54-1, 2014 gozd, traj ni trav nik in podob nih nein ten ziv nih tipih rabe tal, kot je bilo nave de no è tudi pri rezul ta tih vizual ne ana li ze v prej{ njem poglav ju. Obmo~ ja zno traj raz re da 1 smo poi me no va li obmo~ ja z vi so kim relief nim poten cia lom za nek da nje odla ga li{ ~e odpad kov. Sli ka 5: Geo mor fo me tri~ na kla si fi ka ci ja rav nin ske ga relie fa. Glej angle{ ki del pris pev ka. 6 Raz pra va in skle pi Na pod la gi rezul ta tov ugo tav lja mo, da sta za dolo ~a nje z od pad ki zapol nje nih kotanj upo rab ni obe pred - stav lje ni meto di vizual ne inter pre ta ci je relie fa. Ven dar le pa je za uspe {no dolo ~a nje popol no ma zasu tih gra moz nic pri mer nej {i pri kaz DMR z ana li ti~ nim sen ~e njem relie fa, pri ~emer je, zara di majh nih relief - nih raz lik med zasu to kota njo in oko li co, pomem ben poka za telj tek stu ra sen ~e ne ga relie fa. Na sen ~e nem relie fu smo odkri li grbi nast relief zasu tih kotanj, ki ga na nesen ~e nem relie fu tè je zaz na mo ali sploh ne zaz na mo. Za dolo ~a nje odla ga li{~ v sta rih stru gah je pri mer nej {i pri kaz relie fa s hip so me tri~ no barv no les - tvi co, saj so poka za telj relief ne raz li ke, ki jih lah ko zaz na mo z vi zual no inter pre ta ci jo. Z zdru è va njem in pre kri va njem rezul ta tov vizual ne (Sli ka 4) in geo mor fo me tri~ ne ana li ze (Sli ka 5), ki so pred stav lje ni na Sli ki 6, ugo tav lja mo, da se 26 od skup no 46 vi zual no raz poz na nih antro po ge nih relief - nih oblik, ki so poten cial na odla ga li{ ~a odpad kov, pokri va z ob mo~ ji viso ke ga relief ne ga poten cia la za nek da nja odla ga li{ ~a odpad kov (Raz red 1). Te antro po ge ne relief ne obli ke lah ko z ve li ko goto vost jo opre - de li mo kot poten cial na odla ga li{ ~a odpad kov. Za dodat no potr di tev rezul ta tov LiDAR ana li ze smo upo ra bi li geo hi sto ri~ ne podat ke o sta rih gra moz ni cah (Breg Valja vec, Gostin ~ar in Smre kar 2011), kjer je pro stor - sko loci ra nih 30 gra moz nic v raz li~ ni stop nji izko pa va nja gra mo za v pre se~ nih letih 1959, 1964, 1975, 1985 in 1994. Sli ka 6: Pri mer ja va rezul ta tov obeh metod (vi zual ne in geo mor fo me tri~ ne ana li ze) in del na potr di tev rezul ta tov z geo hi sto ri~ ni mi podat ki o gra moz ni cah (Breg Valja vec, Gostin ~ar in Smre kar 2011). Glej angle{ ki del pris pev ka. Li DAR podat ki, ki so za ra~u nal ni{ ko mode li ra nje {e ved no zelo zah tev ni (ko li ~in sko obsè ni), so {e ved no naj là je obvla dlji vi z upo ra bo naj raz li~ nej {ih vizua li za cij skih teh nik (Ka lawsky 2009 v: Mle kù 2010). Sled nje so upo rab ne tudi kadar preu ~u je mo manj {a rav nin ska obmo~ ja. Ned vom no pa je veli ko mò no - sti za odkri va nje nek da njih odla ga li{~ odpad kov tudi v so dob nih in pri hod njih geo mor fo me tri~ nih ana li zah LiDAR relie fa. Uspeh pri odkri va nju odla ga li{~ odpad kov z geo mor fo me tri jo pa je naj bolj odvi sen od vrste odla ga li{ ~a, nje go vih relief nih in mikro-re lief nih zna ~il no sti ter rabe tal nad odlo è ni mi odpad ki. Opi - sa na geo mor fo me tri~ na ana li za je upo rab na za dolo ~a nje izbo ~e nih relief nih oblik ter grbi na stih (rah lo izbo ~e nih) mikro-re lief nih oblik, ki so hkra ti poten cial na odla ga li{ ~a odpad kov. Na Sli ki 6 so sled nja ozna - ~e na z rde ~e obrob lje ni mi pro zor ni mi poli go ni, ki pre kri va jo sivo in sivo-mo dro ~rt ka no obmo~ je. Vbo ~e ne in grbi na ste (rah lo vbo ~e ne) relief ne obli ke (na sli ki 6 ozna ~e ne z ~r no obrob lje ni mi beli mi poli go ni), ki so poten cial no tudi odla ga li{ ~a odpad kov, z opi sa no geo mor fo me tri~ no ana li zo niso dolo~ lji ve. Pred stavlja - jo bodi si opu{ ~e ne gra moz ni ce, del no zapol nje ne gra moz ni ce ali sta re stru ge. ^e èli mo iz teh oblik izlo ~i ti poten cial na odla ga li{ ~a odpad kov, je potreb na dodat na geo hi sto ri~ na ana li za in teren sko delo. Pred stav lje na geo mor fo me tri~ na ana li za omo go ~a naj bolj {e rezul ta te v kme tij ski pokra ji ni s pre vladu - jo ~o kme tij sko rabo tal (nji ve, trav ni ki) kakor tudi na odpr tih povr {i nah brez vid nej {e ga rast lin ske ga pokro va (brez dre ves). Nas prot no pa je meto do lo gi ja sko raj neu po rab na na z dre ve sih pora slih obmo~ jih zno traj kme tij skih zem lji{~ in v goz du saj ima jo podob ne mikro-re lief ne zna ~il no sti kot z od pad ki zapol nje ne gramoz ni ce. ^e èli mo na teh obmo~ jih lo~i ti obmo~ ja antro po ge nih grbi na stih oblik, torej poten cial na odla ga li{ ~a, od narav ne ga grbi na ste ga relie fa, je potreb na dopol nil na ana li za rast lin ske ga pokro va ozi ro - ma ana li za gosto te in vi{i ne dre ves. Upo ra bi mo lah ko letal ske ali sate lit ske posnet ke (npr. infrar de~ sloj) v kom bi na ci ji z Li DAR slo jem vege ta ci je. Na pod la gi rezul ta tov teren ske ga preu ~e va nja rast lins tva na nek - da njih odla ga li{ ~ih odpad kov (Breg Valja vec 2012) pred po stav lja mo, da viso ka in gosto zasa je na dre ve sa uspe va jo na sta bil ni narav ni mati~ ni pod la gi in prsti, ki omo go ~a ta opo ro viso ko ra slim rast li nam. Na povr - {i ni odla ga li{~ (npr. odla ga li{ ~e v za pol nje ni gra moz ni ci), ki so zno traj goz da pa so dre ve sa red kej {a, nì ja 39 Mateja Breg Valjavec, Od kri va nje pri kri tih odla ga li{~ odpad kov v prod ni rav ni ni z geo mor fo me tri~ no ana li zo in LiDAR DMR in grmov ne rasti saj antro po ge na mati~ na pod la ga (nes pri je ti, hete ro ge ni odpad ki) in antro po ge na prst (de po sol) ne omo go ~a ta sta bil ne in kako vost ne rasti gostim in viso kim dre ve som (npr. hrast dob). S pri hod nji mi razi ska va mi je potreb no meto do lo gi jo izbolj {a ti v ok vi ru obsto je ~ih geo mor fo me tri~nih metod, GIS mode li ra nja relie fa, z vpe lja vo dodat nih viso ko-lo~ lji vih podat kov (raba tal, sate lit ski posnet - ki) ter z bolj objekt no usmer je no geo mor fo me tri~ no ana li zo. Samo z opi sa no geo mor fo me tri~ no ana li zo, brez vizual ne ana li ze, lah ko dolo ~a mo samo {ir {a obmo~ ja, ki ima jo relief ne zna ~il no sti, ki so podob ne relie - fu z od pad ki zasu tih kotanj, ne pa natan~ ne lege in obli ke posa mez ne ga odla ga li{ ~a v ko ta nji ozi ro ma kota nje. Upo {te va jo~ geo mor fo lo{ ka izho di{ ~a, na kate rih teme lji pred stav lje ni kon cept odkri va nja pri kri tih, pod - zem nih odla ga li{~, je meto do lo gi ja upo rab na v preu ~e va nju odla ga li{~ v po dob nih alu vial nih obre~ nih rav ni nah (npr. prod nih, ilov na tih), kjer jih je mò no posta vi ti v kon tekst sta rih suhih strug na poplavnih rav ni cah. 7 Lite ra tu ra Glej angle{ ki del pris pev ka. 40 Acta geographica Slovenica, 54-1, 2014, 41–49 SPATIAL AND SOCIAL CHANGES CAUSED BY THE CONTINUOUS EXPLOITATION OF LIGNITE IN THE KOLUBARA LIGNITE BASIN, SERBIA Smiljana \uki~in, Jasmina \or|evi}, Jelena Milankovi} I]VE\RO \AINMS JA Kolubara Lignite Basin. Smiljana \uki~in, Jasmina \or|evi}, Jelena Milankovi}, Spatial and social changes caused by the continuous exploitation of lignite … Spatial and social changes caused by the continuous exploitation of lignite in the Kolubara lignite basin, Serbia DOI: http://dx.doi.org/10.3986/AGS54102 UDC: 913:622.332(497.1) COBISS: 1.01 ABSTRACT: The Kolubara Lignite Basin in the Republic of Serbia is the most important source of this type of fossil energy. Available lignite reserves enable the production of electricity, so the priority, in this region, is its exploitation. This is the reason why all other characteristics of this region have undergone major changes. Since the lignite exploitation started, the land use and river courses have changed in the region, local communities have been moved out, the settlements, infrastructure and human activity have been altered. The whole landscape acquired a completely different image. The social aspect is a sensitive and delicate feature, but the regulation of the region is also significant. Local population in this region has faced a set of social, cultural and economic problems. KEY WORDS: mining, space transformation, regional development, demographic changes, Serbia The article was submitted for publication on October 12, 2012. ADDRESSES: Smiljana \uki~in University of Novi Sad Faculty of Sciences Department of Geography, Tourism and Hotel Management Trg Dositeja Obradovi}a 3, 21000 Novi Sad E-mail: smiljanadjukicinagmail.com Jasmina \or|evi}, Ph. D. University of Novi Sad Faculty of Sciences Department of Geography, Tourism and Hotel Management Trg Dositeja Obradovi}a 3, 21000 Novi Sad E-mail: jasminadjordjevicalive.com Jelena Milankovi} University of Novi Sad Faculty of Sciences Department of Geography, Tourism and Hotel Management Trg Dositeja Obradovi}a 3, 21000 Novi Sad E-mail: milankovicjahotmail.com 42 Acta geographica Slovenica, 54-1, 2014 1 Introduction The influence of mine basins on the environment can be observed through an identification and rela- tivization of development conflicts and harmonization of different conflict interests in the organization and the utilization of the space. In general, almost all the changes which emerge as a result of the impact of mining on the environment are of spatial character. Spatial changes comprise of changes such as tak- ing up huge areas of land for the development of pits, relocation of a watercourse and major traffic and other infrastructures and organization of new settlements for moving the population out of the mining area (Spasi} et al. 2009). Spatial changes are also defined as degraded fields or land, woodland, geother- mal water or other natural elements which have been modified by mining. Cultural potentials which can be modified by the mining include technological heritage, infrastructure, production facilities and hous- ing (Marot and Harfst, 2012). During the process of claiming land for the purpose of surface exploitation, a conflict between of two important activities which are equally treated in most countries: the produc- tion of mineral raw materials and the production of food (Spasi} et al. 2005). Lignite represents, undoubtedly, the most significant energetic potential of the Republic of Serbia. In the Kolubara Basin, there are 20% of geological or exploitation reserves, and the degree of the activity of the deposits is 35%. The availability of the lignite reserves on a relatively small area such as the Kolubara Basin makes it possible to open big pits by keeping the right attitude towards the environment and respect- ing the principles of economic and rational production of energy. The Mining Basin »Kolubara« is the biggest producer of lignite in Serbia with 28–29 million tons a year, which represents 70% of all the coal pro- duced in Serbia (The Spatial Plan … 2008). A significant factor of development on state, regional and town scope is industry, so a great attention should be paid to its location. Well developed areas with properly built infrastructure, abundance of work force and facilities for developers are preferable compared to less developed regions (\uki~in et al. 2011). In Eastern Europe the move of post-communist countries to democracy and markets is unanimous- ly described as »transition«. The theory of transition, therefore, is a natural starting point for understanding post-communist change (Nedovi}-Budi} et el. 2011). The process of industrialization and urbanization refers to the cities and their environments, and it is considered to be the most significant element in the transformation of the geographical environ- ment. The changes in the geographical environment are reflected through the increase of population in the cities, workforce migrations in the direction village-city, transformations in the physiognomic features of cities and their surrounding settlements. The impact of the lignite exploitation on the geographical environment can be observed in the changes in functional structure in cities and their surroundings, as well as in demographic elements. Spatial changes also comprise a set of social changes (Smiljani} 2002). This paper shows spatial and social changes in the Kolubara Lignite Basin which have been created as a result of lignite exploitation and accelerated development of the mentioned area. Due to these trends, the population of the area was exposed to numerous demographic, social and economic changes, which will be presented in the paper. A section of the paper presents the results of a questioning conducted among the population of the settlements situated in the Kolubara Basin. The underlying conditions of lignite mining and utilisation are characterised in the main by the ener- gy management and energy-policy situations and, in particular, the underlying conditions on site – ie in the vicinity of the lignite mines. In Germany, lignite is the most important domestic and subsidy-free source of energy, which, with a share of about one quarter, constitutes a key cornerstone of the energy mix used for power generation (Kulik and Drijver 2012). If the German concept of joint resettlement, mine planning and mining engi- neering, water management, were applied in Kolubara Basin in any form, many social and demographic problems would be avoided. Romania also was faced with lignite exploitation and resettlement in Oltenia. So far, as a result of the lignite open cast opening and extension there were resettled 2200 households, 40 social and cultural constructions (Fodor 2010). Slovenia also has long experience about lignite exploita- tion in Velenje (Marki~ and Sachsenhofer 2010). Velenje region has interesting, preserved natural landscapes, which are suitable for a range of recreational activities and tourism development (Marot and Harfst 2012; Komac et al. 2011; Hose et al. 2011). 43 Smiljana \uki~in, Jasmina \or|evi}, Jelena Milankovi}, Spatial and social changes caused by the continuous exploitation of lignite … 2 The research area The area where exploitation of lignite is conducted in the Kolubara Basin lies 50 km to the south-west of Belgrade, which contributes to its favourable location. The most significant traffic route is the Kolubara River which vertically cuts across the area with the road of first degree and railway route Belgrade–Bar. Moreover, there are numerous smaller regional roads as well as a network of local roads (Todorovi} and Mileti} 2007). The main determinant factors in the success of a region are the fulfilment of the conditions for a good social and economic environment, while it is undoubtedly the case that a healthy environment favouring the growth and deployment of entrepreneurial skills develops more easily in settlements located nearer to larger centres (Ernits 2003). Environment in the Kolubara Basin is not healthy and there are many social and economic disparities. The industrial, mining and energy centres zones/belts and settlements in the prox- imity of traffic corridors and the major urban centres represent areas burdened by numerous environmental problems such as contaminated industrial land, degraded land in the zones of exploitation of mineral raw materials, polluted water and air, plus unsustainable waste management (Miljanovi} et al. 2010). 3 Spatial changes due to lignite exploitation Major differences in well-being among territorial units at subnational level impede the progress of soci- ety and may cause economic, social, urban, environmental and political problems. Acknowledging of regional differences in well-being is of key importance for efficient planning and implementation of regional and spatial policy measures.The most significant conflict of mining industry with the environment in the Kolubara Basin refers to occupying agricultural and forest land in the process of surface exploitation. The occu- pation of land can be permanent or temporary during the exploitation, provided that recultivation brings it back to its original use (Spasi} et al. 2005). The exploitation area of the Kolubara Basin is a dynamic environment where land use changes because of the development of mining activity. According to certain dynamics, the front of mining activity moves, occupying new areas of settlements for the purpose of mining and organisation of traffic and infrastructural corridors, and parts of the pits, where exploitation is finished, are used as dump areas. Dump areas which are completely filled up are technically and biologically recultivated (Spasi} et al. 2009). Terrain inclination and the slope processes are the causes for the occurrence of the landslides and high-intensity soil erosion (Dragicevic et al. 2011; Dragi}evi} et al. 2012). During the opening of surface pits in the Kolubara Basin, the process of decreasing groundwater lev- els was conducted in close vicinity of pits, thus preventing the inflow of groundwater in the work area of the pit. The level of groundwater has decreased (Spasi} et al. 2005). Based on the Plan of General Regulation of the Settlement Vreoci, changes in land use in the central part of the Kolubara Basin up to 2020 will be most evident in the mining and agricultural sectors. In the east- ern part of the Kolubara Basin, agricultural land will also expand but not as much as areas used for mining, since large-scale exploitations are planned. Spatial changes happening due to lignite exploitation in the Kolubara Basin, in addition to changes of land, land use and the groundwater levels, also cause changes in riverbeds. In the Kolubara Basin, there have been major relocations of the Kolubara riverbed as well as regula- tions of its watercourse (Spasi} et al. 2009). The first huge intervention in Kolubara river system happened in 1959, when the Kolubara's riverbed was diverted into its right tributary Pestan River. Those construc- tion works were done for the purpose of lignite exploitation, which permanently influenced the entire process of fluvial erosion: stronger bank erosion resulted in larger amounts of sediment yield (Roksandic et al. 2011). The Kolubara river has been relocated further and regulated because of the opening of the pit »Tamnava – Isto~no polje«. In the period 1975–1977, the relocation and regulation of the Kolubara was conducted within the opening of the surface pit »Tamnava – Isto~no polje« and its protection from flooding. The per- formed protection activity of SP »Tamnava – Isto~no polje« against floods from the Kolubara and its left tributaries, the river Vrani~ina and the brook Skobalj, consists of relocating the Kolubara riverbed in the area from the railway bridge Vreoci – Obrenovac (km 28 + 880) to the Vrani~ina estuary (km 37 + 380) and building protective embankments. Significant morphological changes on the Kolubara and Pe{tan 44 Acta geographica Slovenica, 54-1, 2014 N W E S NORTH NORTH BAČKA BANAT WEST BAČKA CENTRAL SOUTH BANAT BAČKA Exploitation areas and mining SREM SOUTH BANAT CITY OF MAČVA BELGRADE PODU- BRANIČEVO NAV- LJE BOR KOLUBARA ŠUMADIJA POMO- MORA- RAVLJE VICA ZAJEČAR RAŠKA RASINA ZLATIBOR NIŠAVA TOPLICA PIROT KOSOVSKA JABLANICA MITROVICA PEĆ KOSOVO Author of contents: KOSOVO PČINJA -POMO- S. Đukičin, J. Milanković RAVLJE Author of map: S. Đukičin, J. Milanković PRIZREN Source: Wikipedia, Districts of Serbia (http://en.wikipedia.org/wiki/Districts_of_Serbia) 100 km Figure 1: The position of the Kolubara Lignite Basin (Internet 1). 45 Smiljana \uki~in, Jasmina \or|evi}, Jelena Milankovi}, Spatial and social changes caused by the continuous exploitation of lignite … I]VE\RO \AINMS JA Figure 2: Kolubara D field. happened in 1976. Moving the course of the Kolubara was aimed at widening the strip mining of lignite (Dragi}evi} et al. 2007). The River Pe{tan was regulated in its lower course, from the Kolubara estuary (km 0 + 000) to the rail- way bridge Belgrade – Bar (km 3 + 070) in 1981. In the regulated riverbed of the river Pe{tan, from the Kolubara estuary and the Ibar motorway, on the kilometre 1 + 065 a cascade was built to control ver- tical alignment and the completely regulated riverbed in the upstream direction (Dragi}evi} et al. 2007). 4 Social changes in the Kolubara lignite basin Relocating population from the exploitation area in the Kolubara Basin certainly represents the most sig- nificant and the most sensitive change occurring due to a radical development of the industry and economy. Based on numerous questioning (surveys were done by the authors) in this field of study, it has been con- cluded that the population experiences this relocation as an imposition and expresses deep dissatisfaction with it. Over half of the population had to change their profession after relocation, and a huge number of them were left jobless. Changes in demography affect different aspects of both urban and rural areas. Sudden increases in the population may lead to a complete disorganisation of a city or even of a village (Pereira Dra et al. 2010). The exploitation of lignite in the Kolubara Basin started in 1896, and the first open pit mining started in 1952. The largest resettlements began in the last decade of the 20th century when 1614 households were relocated out of the zone of open pits development (Spasi} et al. 2009). According to the Plan of General Regulation for the settlements of Vreoci, Zeoke, Medo{evac and Burovo (2008) up to 2020, the most inten- sive relocations will be conducted in the settlements of Vreoci (1006 households), Zeoke (177 households), Medo{evac (145 households) and Burovo (43 households) (Luki} and Matijevi} 2006). 46 Acta geographica Slovenica, 54-1, 2014 9000 Agricultural population 8000 7664 Population engaged in mining 7339 7000 6000 5343 5000 4000 3000 1877 2000 1407 1297 1000 543 87 0 Lazarevac Obrenovac Lajkovac Ub Munucipality Municipality Municipality Municipality Figure 3: Agricultural population and population engaged in mining according to 2002 census (Republi~ki zavod za statistiku … 2004). Since the most intensive relocation of the population has been conducted and planned in the settle- ment of Vreoci in the municipality of Lazarevac, the phenomenon of relocation will be specially treated in the case study of this settlement which can be used as guidelines for all other settlements with similar plans. The population of Vreoci has largely urban socio-economic features, with a relatively high level of activity for both genders, aging processes, etc. Most of the employees work in one of the facilities of the Mining Basin »Kolubara«. Relocations were conducted through the process of expropriation, most often through payments for the taken properties, and the households had to solve the problem of the new place of res- idence on their own. By 2015, 95% of population from Vreoci will be resettled, and 18% from settlement [opi} (The Plan of General … 2008). Accelerated process of demographic aging of the population will cause further disappearance of sin- gle households, which will contribute to the fall in the total number of village households which are affected not only with this problem, but also with the problem of relocation (Luki} and Matijevi} 2006). Twenty of respondents were interviewed at their homes. They were asked about their social and eco- nomic situation. Due to aging, relocation and negative population growth in the settlements of the Kolubara Basin, a series of demographic, social and economic problems are projected in the next periods. In the relo- cation of the population, the most affected are people without qualifications and those who are not ready enough to adjust to a new environment. During the research among the population for the purpose of this paper, they stated that they received large sums of money for the expropriated properties, but at the same time they lost the roof over their heads. In this manner, a great number of people without adequate qual- ifications are threatened to become social cases. In addition to demographic problems in the process of intensive exploitation, there are key changes in the network of settlements. Disturbing the functional organ- isation of settlements and traditionally formed village communities is a special problem which, in spite of material and other reimbursements, can be resolved only by the change in generations (Spasi} et al. 2007). 47 Smiljana \uki~in, Jasmina \or|evi}, Jelena Milankovi}, Spatial and social changes caused by the continuous exploitation of lignite … Finding locations for new settlements represents a very complex process, regarding the fact that the relo- cation of settlements is accompanied by problems related to: redistribution of functions among settlements, resulting in the transformation of the network of settlements; limited possibilities of resettlement of the min- ing basin after the completed exploitation, resulting in an uninhabited area; the stability of the landfills after the completion of mining works; the fact that the population does not want to be relocated to remote locations, which represents a problem because in large lignite basins, the pits are usually developed con- tinually along a huge territory; and the principles of rationality which impose relocation of the population within the existing settlements. This decreases investment in settlement organisation and the construc- tion of buildings with public functions, but there is also a problem of accepting new population by the domestic population, i. e. the adaptation of the new population (Spasi} et al. 2009). 5 Conclusion Modern human activity often influences the change of the space. Most often these changes are stressful for the spatial and social elements. In addition to planned projects and activities, it is not rare to have some failures. Exploitation in the Kolubara Lignite Basin is on the list of priorities because of its significance. This attitude of responsible institutions in Serbia causes permanent and radical changes in the area. A ques- tion is often asked if it is good to transform an area so that its land use and river courses are drastically changed, population relocated? What are the effects of these endeavours and what is the future for such an area? Due to lignite exploitation, settlements were relocated, and the population faced numerous social and economic problems. The Republic of Serbia is the country which has not overcome the transition yet and which still does not have economic and other instruments to help it handle conflict situations like the one in the Kolubara Basin in the right way. The need for energy products exploitation is understandable, but, at the same time, relocation of the population and settlements should not be dealt with so easily. Due to one activity in an area, other activities should not be neglected. All activities should be conducted accord- ing to a plan, with good calculations and with the least number of negative effects. The Kolubara Basin is not the best example of these activities. In these activities Serbia should follow the example of well organ- ised lignite exploitation country like Germany (Kulik and Drijver 2012). 6 Acknowledgement This paper was financed by Project 176020 of the Serbian Ministry of Education, Science and Technological Development, and by Project (114-451-1861/2011-02) of the Provincial Secretariat of Science and Technological Development of the Vojvodina Province. 7 References Dragi}evi}, S., Carevi}, I., Kostadinov, S., Novkovic, I., Abolmasov, B., Milojkovi}, B., Simi}, D. 2012: Landslide susceptibility zonation in the Kolubara river basin (western Serbia) – analisys of input data. Carpathian Journal of Earth and Environmental Sciences 7-2. Dragicevic, S., Filipovic, D., Kostadinov, S., Ristic, R., Novkovic, I., Zivkovic, N., Andjelkovic, N., Abolmasov, B., Secerov, V., Djurdjic, S. 2011: Natural Hazard Assessment for Land-use Planning in Serbia. International journal of environmental research 5-2. Dragi}evi}, S., @ivanovi}, N., Duci}, V. 2007: Faktori nastanka poplava na teritoriji op{tine Obrenovac. Zbornik radova – Geografski fakultet Univerziteta u Beogradu 55. Beograd. Ernits, R. 2003: Location as the reason for the problems of old industrialised settlements. European journal of spatial development 4. Stocholm. Fodor, D. 2010: Mining industry and environment. Revista Minerol 16-8. Petrosani. Hose, T., Markovi}, S., Komac, B., Zorn, M. 2011: Geotourism – a short introduction. Acta geographica Slovenica 51-2. DOI: http://dx.doi.org/10.3986/AGS51301 Internet 1: http://en.wikipedia.org/wiki/Districts_of_Serbia (10. 1. 2012) 48 Acta geographica Slovenica, 54-1, 2014 Komac, B., Zorn, M., Erharti~, B. 2011: Loss of natural heritage from the geomorphological perspective – Do geomorphic processes shape or destroy the natural heritage? Acta geographica Slovenica 51-2. DOI: http://dx.doi.org/10.3986/AGS51305 Kulik, L., Drijver, J. 2012: Holistic planning and approval of sustainable lignite mining and utilisation. Coal International 260-2. Luki}, V., Matijevi}, D. 2006: Demografski i prostorno – funkcionalni procesi u seoskim naseljima Ljiga. Zbornik radova geografskog instituta »Jovan Cviji}«, SANU 55. Marki~, M., Sachsenhofer, R. 2010: The Velenje lignite – its petrology and genesis. Ljubljana. Marot, N., Harfst, J. 2012: Post-mining potentials and redevelopment of former mining regions in Central Europe – Case studies from Germany and Slovenia. Acta geographica Slovenica 52-1. Ljubljana. DOI: http://dx.doi.org/10.3986/AGS52104 Miljanovi}, D., Mileti}, R., \or|evi} J. 2010: Regional inequality in Serbia as a development problem. Acta geographica Slovenica 50-2. DOI: http://dx.doi.org/10.3986/AGS50204 Nedovi}-Budi}, Z., Djordjevic, D., Dabovi}, T. 2011: The Mornings after … Serbian Spatial Planning Legislation in Context. European planning studies 19-3. Pereira Dra, D., Recio, S. and Gonsalo, J. C. 2010: Evolution of the landscape as a response of a demographic change. A case study in the Duero riverside, Spain. Local environment 15-5. Plan generalne regulacije za naselje Vreoci 2008 Beograd: Slùbeni glasnik grada Beograda 54. Plan generalne regulacije naselja Medo{evac, Zeoke i Burovo 2008 Beograd: Slùbeni glasnik grada Beograda 58. Prostorni plan podru~ja eksploatacije Kolubarskog lignitskog basena 2008 Beograd: Slùbeni glasnik Rebuplike Srbije 122. Republi~ki zavod za statistiku 2004 Beograd: Delatnost i pol aktivnog stanovni{tva koje obavlja zanimanje knjiga 6. Roksandic, M., Dragicevic, S., Zivkovic, N., Kostadinov, S., Zlatic, M., Martinovic, M. 2011: Bank erosion as a factor of soil loss and land use changes in the Kolubara River Basin, Serbia. African journal of agricultural research 6-32. Smiljani}, Z. 2002: Savremene tendencije procesa urbanizacije Kolubarskog okruga. Zbornik radova – Geografski fakultet Univerziteta u Beogradu 50. Spasi}, N., Petovar K., Joki} V. 2007: Transformation of Settlements and Population in large lignits Basins. Spasi}, N., Stojanovi}, B., Nikoli}, M. 2005: Uticaj rudarstva na okruènje i revitalizacija degradiranog pros- tora. Arhitektura i urbanizam 16–17. Spasi}, N., Dùni}, J., \ur|evi}, J. 2009: Konflikti i ograni~enja u prostornom razvoju rudarskih basena. Arhitektura i urbanizam 27. Todorovi}, M., Mileti}, R. 2007: Kori{}enje zemlji{ta u Valjevskim selima Buja~i}, Klinci i Petnica. Zbornik radova Geografskog instituta »Jovan Cviji}« SANU 56. \uki~in, S., Milankovi}, J., \or|evi}, J. 2011: Contemporary Business Trends and Industrial Transformation in Slovenia on the Examples of Maribor and Celje. Geographica Pannonica 15-3. 49 50 Acta geographica Slovenica, 54-1, 2014, 51–65 POPULATION GROWTH IN THE BORDER VILLAGES OF SREM, SERBIA Tamara Luki}, Milka Bubalo - @ivkovi}, Bojan \er~an, Gordana Jovanovi} NA^RE \N JAOB Children in the village Biki} Do. Tamara Luki}, Milka Bubalo - @ivkovi}, Bojan \er~an, Gordana Jovanovi}, Population Growth in the Border Villages of Srem, Serbia Population Growth in the Border Villages of Srem, Serbia DOI: http://dx.doi.org/10.3986/AGS54103 UDC: 911.373:314.116(497.11) COBISS: 1.01 ABSTRACT: Population growth in the border villages of Srem (Vojvodina, Serbia) has been analysed in this paper, with the goal of explaining how and why it differed from other areas in the region. Special atten- tion has been paid to the 1990s, because these villages became part of a border region and a high level of migration on the territory of the former Yugoslavia occurred, much of it through this territory. The results of the research are derived from literary resources and applying mathematical and statistical procedures in the processing of data received from the Statistical Office of the Republic of Serbia. They were checked on the field via a questionnaire. This paper is significant because it enriches knowledge about villages of Srem, the municipality of [id and population trends at the end of the 20th century. KEY WORDS: Serbia, Srem, Municipality of [id, population growth, immigration, border rural settlements, ethnic composition The article was submitted for publication July 1, 2011. ADDRESSES: Tamara Luki}, Ph. D. Faculty of Science University of Novi Sad Trg Dositeja Obradovi}a 3, 21 000 Novi Sad, Serbia E-mail: snstamaraayahoo.com Milka Bubalo - @ivkovi}, Ph. D. Faculty of Science University of Novi Sad Trg Dositeja Obradovi}a 3, 21 000 Novi Sad, Serbia E-mail: miladin32dusayahoo.com Bojan \er~an Faculty of Science University of Novi Sad Trg Dositeja Obradovi}a 3, 21 000 Novi Sad, Serbia E-mail: bojandjercanayahoo.co.uk Gordana Jovanovi}, Ph. D. Faculty of Science University of Novi Sad Trg Dositeja Obradovi}a 3, 21 000 Novi Sad, Serbia E-mail: gordanagjovanovicayahoo.com 52 Acta geographica Slovenica, 54-1, 2014 1 Introduction With the collapse of Yugoslavia at the beginning of the 1990s, new borders were established, and consequently border villages. Literary sources (Penev 1994; Kova~evi} 2006; Kova~evi} etal. 2009; Ivkov-Dìgurski et al. 2010) mention problems of the new border villages in Serbia. Among them in particular are demographic prob- lems, such as depopulation, emigration, the ageing of the populace etc. (Vujadinovi} et al. 2010). These problems also appear in other parts of Europe, according to other sources (Machold et al. 2002; Ni Laoire 2000; Stockdale 2002, 2006). This research on the population trends in the border villages of Srem had as its goal the determina- tion of the parameters of the population movement and thereby illustrating to what extent drawing the border had in demographic sense positive or negative influence on these villages. For that reason, par- ticular attention has been paid to the period between the last two censuses. \ur|ev et al. (2004) stated that according to the 2002 census refugees and displaced persons from the region of the former Yugoslavia caused regional differences in the growth rate of the population of Vojvodina. The share of this catego- ry of people in the total population in the municipality of [id, in 2002, had the highest value at 23.4%. Given that the wartime operations in Croatia and Bosnia and Herzegovina stopped in the mid 1990's, it must be assumed that there were even more of people present at that time but many of them lost their refugee status by obtaining citizenship. Srem, one of three regional units of the Autonomous Province of Vojvodina, has fourteen border set- tlements (VGI 1982; 1982a; 1982b; 1983). From that number, two border villages (Ne{tin and Vizi}) are Legend N Border Border crossing Highway E-70 BAČKA PALANKA Regional road Danube Local road Railway track Molovin River BEOČIN Bikić Do Stream or canal Berkasovo Sot Ljuba Municipality center ŠID Privina Ilinci Settment in Šid municipality Glava Erdevik Gibarac Vašica Bingula Bačinci Adaševci Kukujevci Batrovci RUMA C R O A T I A Morović Višnjićevo SREMSKA MITROVICA Jamena Sava BOGATIĆ B O S N I A A N D H E R C E G O V I N A 0 10 20 30 km ŠABAC Author of contents/avtor vsebine: Tamara Lukić Author of map/avtorica zemljevida: Tamara Lukić Source/vir: Geografska karta Vojvodine, 2001; RZS, 2004 Figure 1: Geographic position of settlements in the municipality of [id. 53 Tamara Luki}, Milka Bubalo - @ivkovi}, Bojan \er~an, Gordana Jovanovi}, Population Growth in the Border Villages of Srem, Serbia part of the municipality of Ba~ka Palanka (Bogdanovi} et al. 1997), one (Sremska Ra~a) is located in the municipality of Sremska Mitrovica (]ur~i} et al. 2002) and eleven settlements (Figure 1) are part the municipality of [id (]ur~i} 2001). Considering the fact that most of the settlements are located in the municipality of [id, because of the factors of standardisation of local self-management performance, this paper will be focused only on these villages. According to the categorisation of settlements by Statistical Office of the Republic of Serbia, only one of eleven settlements in the municipality of [id has been deemed to be a štown settlement’ (Statistical Office of the Republic of Serbia, 2004a). The multi-functionality of this settlement, which is simultaneously the municipality centre, puts other villages into an unequal posi- tion. The administrative and management functions of the settlement imply the presence of other functions, e.g. educational, cultural, etc., and in that way positively modify the demographic situation. For that rea- son, [id will be excluded from the analysis, and only village settlements will be compared. 2 Material and methods This paper is the result of analyses of data received at the Statistical Office of the Republic of Serbia. Data were illustrated by drawing maps: relevant content was extracted from existing figures, in order to form the desired maps. The results of the research were verified on the field by conducting a questionnaire for one hundred respondents, i.e. an interview was conducted with ten respondents in each village. Respondents were between the ages of 19 and 65, and both sexes were equally represented. The aim of the interview was to explain some occurrences observed in the analysis and processing of statistical data. For that reason, the ques- tions were of an open character, and answers to them were not predictable. 3 Results and discussion The analyses of the population trends should find and explain differences in the movements of people in the border villages of the municipality of [id in the period from the census in 1991 to the census in 2002. In addition to the explanation will be a discussion of the ethnic structure of the population, and the results of the conducted interview. 3.1 Population figures An international recommendation was accepted that the census be carried out every ten years, in the first year of the decade; this has been the practice since 1961 (Stankovi} 2006). Because the census that should have been carried out in 2001 was made in 2002, the comparability of census data was seriously dam- aged; nevertheless, certain tendencies in population trends could be observed (\ur|ev et al. 2010). According to the 1991 census, the population of the border villages in this area ranged from 299 inhab- itants, registered in Biki} Do, to 2105 inhabitants in Morovi}. Differences in the population sizes of villages were preserved in the most recent census: in 2002, they ranged from 298 inhabitants in Molovin to 2164 inhab- itants in Morovi}. Analyses of the geographical position and relief characteristics show that border villages with smaller populations are located in the northern half of the border, i.e. on the slopes of the Fru{ka Gora mountain and in river valleys of its streams. Only Batrovci differs from this trend; it is located on the Bosut River, somewhat north of the E-70 motorway. None of the villages has changed the category of size to which they belonged, but within the categories certain changes occurred (Table 1). Table 1: Classification of border villages of the municipality of [id according to the size and according to the 1991 and 2002 censuses. Census ≤ 500 500–1000 1000–1500 1500–2000 2000 ≥ 1991 3 3 2 1 1 2002 3 3 2 1 1 Source: Statistical Office of the Republic of Serbia, 2004a 54 Acta geographica Slovenica, 54-1, 2014 In the period when the aforementioned border villages were not border villages, the population decreased in all villages from the 1981 census to the 1991 census. That decrease was –9.2% in average and was three times higher than the value calculated for the municipality [id (–3.1%). The decrease in the population ranged from –0.7% in Biki} Do to –18.7% in Molovin (Figure 2). There was no decrease in the number of inhabitants in the town of [id. Characteristic migrations, for the decade of 1981–1991, which were ini- tiated in earlier decades by the processes of urbanisation, industrialisation and suburbanisation, continued to occur (Luki} 2010, 2). The development of secondary and tertiary businesses in the municipal and region- al centres, such as [id, increased the population from 1981 to 1991 by 5.8%. However, in the period from 1991 to 2002, four of the ten observed villages showed increases in pop- ulation (Figure 2). During the analysis of the geographic position of these border villages, the conclusion was drawn that population number increased in villages that are located on the highway M 18.1 (Biki} Do and Berkasovo), which connects [id and Ba~ka Palanka, and in villages that are located on crossroads for other municipality villages (Va{ica, Morovi}). Border villages that did not have an increase in popu- lation are not located on these transit lines. The population decreases in those villages ranged from –0.4% in Sot to –12.7% in Jamena. Consequently, it was concluded that, although a decrease was noticed, its inten- sity is smaller than in the decade that preceded (Table 2). The increase in the number of inhabitants in the border villages (2.2%) is less than a fourth than that on the municipal level (9.8%). Given that the number of inhabitants in the town of [id increased by 15.2%, it can be concluded that the municipal centre was more attractive for settlement than other municipal rural settlements that were not on the border. 3.2 Population trend Changes of the values of population were explained in parameters of population trends, i.e. rates of nat- ural population growth and migration balance were calculated. 3.2.1 Natural movement According to the rate of natural population growth, among the border villages of the municipality of [id there are three types of villages: villages that did not register positive natural population growth in the observed period, from 1991 to 2001 (Va{ica, Ilinci, Jamena and Sot), villages that registered positive natural popu- lation growth in one year (Batrovci, Berkasovo and Morovi}) and villages that had positive natural population growth in four of ten years (Molovin, Ljuba and Biki} Do) (Table 3). Table 2: Population number of border villages in the municipality of [id. Settlement Year Change in absolute number Change in relative number (in %) 1981 1991 2002 1991/1981 2002/1991 1991/1981 2002/1991 Batrovci 464 399 361 –65 –38 –16.3 –10.5 Berkasovo 1217 1103 1258 –114 155 –10.3 12.3 Biki} Do 301 299 336 –2 37 –0.7 11.0 Va{ica 1740 1636 1758 –104 122 –6.4 6.9 Ilinci 1011 883 843 –128 –40 –14.5 –4.7 Jamena 1577 1399 1241 –178 –158 –12.7 –12.7 Ljuba 639 585 563 –54 –22 –9.2 –3.9 Molovin 362 305 298 –57 –7 –18.7 –2.3 Morovi} 2196 2105 2272 –91 167 –4.3 7.4 Sot 900 819 816 –81 –3 –9.9 –0.4 Villages* 10407 9533 9746 –874 213 –9.2 2.2 Town ([id) 13450 14275 16834 825 2559 5.8 15.2 Municipality** 37459 36317 40255 –1142 3938 –3.1 9.8 Note: Villages* – 10 border villages of the municipality of [id; Municipality** – all (19) settlements of the municipality of [id; Source: Statistical Office of the Republic of Serbia, 2004a; own calculations. Figure 2: The change in the population (in %) in the border villages of the municipality of [id, according the 1981–2002 censuses. p p. 56 55 Tamara Luki}, Milka Bubalo - @ivkovi}, Bojan \er~an, Gordana Jovanovi}, Population Growth in the Border Villages of Srem, Serbia AICV Y OR LIT IT M IPA A IC A K N K Y S U 1 N M M LIT 2 E LA R IPA S PAA ICN 3 KČ U Y AB M 4 LIT 5 6 IPA A D IC N I N 7 NU 4 V 1 M A O 8 ID G Š I A 2 E 0 1 N 1 2 S Z R /0 I A f Srem 1 O 1 T E 9 1 9 B H 9 ts o A 1 en O ača RC o voo a a R vin vci vić 3 sk a 1 b lo ić D ci ro en er settlem eštin t o o izić ju o ik ersak ašica atro rd V L S M B B Šid N Ilin V B M Jam Srem N o . . . . . . . . . . . . . . B 1 2 3 4 5 6 7 8 9 0 1 2 3 4 1 1 1 1 1 AICV Y OR LIT IT M IPA A IC A K N K Y S U N 1 M LIT 2 E M LA R IPA S PAA ICN 3 KČ U Y AB M .4 LIT 5 6 IPA A 4 D 0 IC 0 1 N N I N 7 U 4 , 2 /9 1 V SZ 1 M A 8 O ID m ; R 9 8 G 1 1 Š 2 I A k 0 0 1 E 0 0 1 N 3 Z I A S e, 2 R T 9 1 O in 1 B E ić d A H ku O ić jvoo ality k RC ara L u icip e village area 3 arta V n 1 am ara L u f th 5 n ) 1 a k ) ) ts: T am f m % % 5 % 0 ary o latio 5 1 2 ten : T rafsk er o d u % % n ap g n n p ) 0 5 % % (– (– (– rd u o 2 1 0 % 0 – – – eo o o w % – 1 – 0 0 o – 5 5 p f co f m 5 – 5 1 1 1 B B T 0 – 1 1 5 0 – – – – d r o r o o o ge in er (in rce: G b th th 8 u u uo egen an m 0 A A S L h u C n 56 Acta geographica Slovenica, 54-1, 2014 Table 3: Changes of the rate of natural population growth (in ‰) in border villages of the municipality of [id in the period between 1991 and 2001. Settlement 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 Batrovci –4.4 –6.7 –13.5 –18.3 –18.6 –7.1 4.8 –12.2 –24.7 –20.1 –20.2 Berkasovo –5.0 –8.4 –5.1 –5.1 –3.5 –11.3 –17.6 5.3 –20.6 –13.6 –13.4 Biki} Do –19.9 –13.3 0.0 –10.0 –3.3 –3.3 –3.3 10.0 10.0 10.0 6.6 Va{ica –1.7 –6.4 –7.0 –4.7 –9.5 –7.8 –12.0 –9.7 –7.9 –14.1 –14.6 Ilinci –17.0 –12.2 –2.1 –11.5 –18.0 –18.2 –6.5 –8.8 –20.1 –6.8 –17.1 Jamena –7.1 –12.3 0.0 –10.6 –8.8 –11.6 –9.7 –11.2 –14.8 –5.7 –14.5 Ljuba 6.3 –11.1 –9.6 –9.7 –13.1 –16.5 0.0 1.7 –1.7 3.4 3.4 Molovin 2.8 –8.6 –8.7 0.0 –15.0 3.1 0.0 –12.7 –6.4 3.3 6.6 Morovi} –3.7 –7.8 –5.1 –6.0 0.0 3.7 –11.7 –5.7 –6.1 –6.2 0.0 Sot –13.5 –12.5 –14.9 –11.5 –2.3 –10.6 –14.2 –3.6 –13.3 –19.5 –22.0 Villages* –6.3 –9.9 –6.6 –8.7 –9.2 –8.0 –7.0 –4.7 –10.6 –6.9 –8.5 Town ([id) 2.1 0.2 2.4 –1.5 1.2 1.4 –1.1 –2.1 –1.4 –1.7 –1.0 Municipality** –2.0 –4.9 –3.0 –4.8 –4.1 –3.3 –5.1 –3.1 –6.1 –5.2 –5.4 Note: Villages* – 10 border villages of the municipality of [id; Municipality** – all (19) settlements of the municipality of [id; Source: Statistical Office of the Republic of Serbia, 2004a; Statistical Office of the Republic of Serbia, 2010; own calculations From the border villages of Srem that were singled out as those in which the population increased, only Biki} Do distinguished itself also as one in which positive natural population growth was registered and has occurred continuously during previous four years (Figure 3). In other border villages, the changes of population were mainly influenced by mechanical population movement. The town`s population growth rate in the first half of the observed decade, except for 1994, had a pos- itive value, followed by a negative one. Positive population growth could not compensate for the volumes of negative rates in municipal settlements, so the population growth rate at the municipal level, had per- manent negative values in the observed period, showing a negative growth tendency. Thus, population growth could be the result of a solely mechanical movement of population, i.e. immigration. 30 Birth rate Death rate Natural growth 25 20 15 10 )‰ 5 0 Rate (in –5 –10 –15 –20 –251990 1992 1994 1996 1998 2000 2002 Year Figure 3: Changes of the rate of natural population growth of Biki} Do in the period between 1991 and 2001 (Statistical Office of the Republic of Serbia, 2010; own calculations). 57 Tamara Luki}, Milka Bubalo - @ivkovi}, Bojan \er~an, Gordana Jovanovi}, Population Growth in the Border Villages of Srem, Serbia 3.2.2 Migrations Migration into Europe has been on the rise in recent decades (Hooghe et al. 2008; Meuleman et al. 2009). Regions of the former Yugoslavia, to which the border villages of the municipality of [id also belong, have followed this trend in their own way. This is the best illustrated by analysing the proportions of immi- grant populations. According to the 2002 census, the immigrant population constitutes the majority in the municipality of [id (56.3%), as well as in the town (57.1%) and in the border villages (52.9%). Specifically, the portion of the population that has lived in the border villages of the municipality of [id from their birth, the so-called natives, differs greatly, ranging from 36.7% in Morovi} to 63.7% in Ljuba (Table 4). Border villages in the municipality of [id in which less than 50% of the people are natives are those vil- lages that have increased their populations. From other border villages, only Sot is part of this group. In all the border villages of the municipality of [id, the majority of the immigrant population is com- prised of people who have migrated from the territories of former Yugoslav republics, other than Serbia (Luki} and Matijevi} 2006). Except the village Ljuba, their portion in the total immigrant population exceeds 50% (Table 5). The share of the immigrant population on the municipal level (63.3%) and on at the town level (52.1%), is lower than the share in the border villages of the municipality of [id (69.7%). Refugees are those people who do not plan to migrate, but they are suddenly forced to do so, and consequently they make little preparation and generally do not know their destination (O'Docherty Madrayo 1988). In the inter- views, it was concluded that for most of the immigrant population, and almost 100% of the female respondents, the main reason for migration was the fear of potential violence, i.e. war trauma. This fact is concurrent with the research results Lim et al (2007; 1542) and Vrecer (2010, 499). In the questionnaire, one of the questions referred to the factors that crucially affected the immigrants' choice to migrate to a certain village. The answers were different, but among them the most frequent were the following: in some villages they already had relatives, rarely friends; in some villages, the prices of real estate were more favourable; some villages, for example on the slopes of the Fru{ka Gora mountain, had similar landscape characteristics to the area they came from, i.e. for those from hilly terrain, it is more difficult to adjust to life on the plains and vice versa; personal reasons, for example forming the family, etc. Some of these answers coincide with the results of Pilkington (1998) and Luki} and Nikitovi} (2004). In some of the border villages, significant portions of migrants who did not come from the territories of former Yugoslavia stand out. For example, 43.3% of migrants in Biki} Do and 35.3% in Berkasovo are settled populations of intra-municipal migrations. In the interviews, it was stated that the reason many migrat- ed from other municipal villages to Biki} Do or to Berkasovo was that these places are populated by Rusyn minority, and some of the respondents think that Rusyns settle in these villages for the reason of marriage. In Ljuba, it has been recorded that more than one third of the settled population (33.5%) are migrants who settled from the territories of other municipalities in the Republic of Serbia. In interviews it was found Table 4: Share of natives in total population, according the census 2002 in the border villages of the municipality of [id. Settlement Sum Natives Immigrants Number % Number % Batrovci 320 193 60.3 127 39.7 Berkasovo 1228 475 38.7 753 61.3 Biki} Do 336 158 47.0 178 53.0 Va{ica 1717 842 49.0 875 51.0 Ilinci 827 478 57.8 349 42.2 Jamena 1130 586 51.9 544 48.1 Ljuba 559 356 63.7 203 36.3 Molovin 298 170 57.0 128 43.0 Morovi} 2164 794 36.7 1370 63.3 Sot 791 360 45.5 431 54.5 Villages* 9370 4412 47.1 4958 52.9 Town ([id) 16311 7004 42.9 9307 57.1 Municipality** 38973 17019 47.3 21954 56.3 Note: Villages* – 10 border villages of the municipality of [id; Municipality** – all (19) settlements of the municipality of [id; Source: Statistical Office of the Republic of Serbia, 2004b; own calculations 58 Acta geographica Slovenica, 54-1, 2014 out that Ljuba is settled by the Slovak minority, and that these migrants have origins in the municipality Kova~ica (Padina and Kova~ica settlements), Ba~ki Petrovac (Ba~ki Petrovac, Gloàn and Silba{ setllements), Beo~in (the village of Lug), Stara Pazova (Stara Pazova settlement) and Ba~ (the village of Selen~a) and others, i.e. from municipalities settled by Slovaks. Moreover, while talking with the local population, it was determined that Slovaks cherish their relations with their mother-land and that part of the marriage migrations happen between Ljuba and villages in Slovakia. This directly explains the fact that this village has the highest percent of people from the territories of other countries compared to other border vil- lages of the municipality [id (Table 5). In the second place according to the level of migrant origin are those that have settled in the area as a result of intra-municipal migration. Such people represent nearly one in three immigrants (30.3%) in the town of [id and one in five in the municipality (21.0%). According to Luki} and To{i} (2011, 322), the current economic reforms, the process of deindustrialisation and the privatisation of larger enterprises have been significant for changes in the commuting flows (directions and structure). The increase in the num- ber of commuters in Serbia is one of the ways in which the population is adapting and overcoming the problems of unemployment and the lack of adequate jobs in the local milieu, while simultaneously maintaining of commuting as the form of mobility that prevents further concentration of people in urban centres. The fea- tures of a municipality attract residents, but they change their place of residence towards other municipal settlements šin search of bread’. Based on the interviews, it was found that the jobs in the food-processing indus- try (Molovin and Berkasovo Wineries, šAgropapuk’ in Kukujevci, šBig Bull’ in Ba~inci, etc.) appeared in rural settlements and thus they became the gravitational point for the working age population of the municipality. Table 5: Share of migrants according to their origin, in total migrants (in %), according to the 2002 census in the border villages of the municipality of [id. Settlement Sum Same Other Other Former YU Other Unknown municipality municipality countries*** republics countries Batrovci 127 13.4 7.9 5.5 72.4 0.0 0.8 Berkasovo 753 35.3 8.2 2.4 52.7 0.5 0.9 Biki} Do 178 43.3 5.6 0.0 50.6 0.0 0.5 Va{ica 875 18.3 4.0 2.1 75.1 0.3 0.2 Ilinci 349 19.5 7.2 2.9 69.9 0.0 0.5 Jamena 544 6.6 3.7 4.2 83.8 0.7 1.0 Ljuba 203 18.2 33.5 0.5 45.8 1.0 1.0 Molovin 128 21.1 11.7 4.7 61.7 0.8 0.0 Morovi} 1370 14.2 6.0 4.5 74.2 0.7 0.4 Sot 431 13.0 6.5 1.6 77.0 0.5 1.4 Villages* 4958 18.9 7.2 3.0 69.7 0.6 0.6 Town ([id) 9307 30.3 10.0 6.1 52.1 0.8 0.8 Municipality** 21954 21.0 9.6 4.5 63.3 0.8 0.8 Note: Villages* – 10 border villages of the municipality of [id; Municipality** – all (19) settlements of the municipality of [id; other republics*** – Montenegro (During the 2002 census, Serbia and Montenegro constituted Federal Republic of Yugoslavia (1992–2003)); Source: Statistical Office of the Republic of Serbia, 2004b, own calculations. Shares of migrants in border villages of the municipality of [id show that the majority of this part of the population of every village was settled during the 1990s, ranging from 27.8% in Jamena to 77.0% in Sot (Table 6). The period between 1946 and 1960 relates to the time of colonisation, which was conducted according to the Law on Agrarian Reform and Colonisation from 1945, by which population from hilly terrain of the former Yugoslavia (Ga}e{a 1984, 113; ]upurdija 1998, 225), i.e. from the same territory as from the observed decade (1990s), settled the territory of Vojvodina. The highest shares of population settled in that period were found in the southern border villages Jamena (25.6%) and Batrovci (23.6%). In the migrant population, two groups have de facto been singled out: migrants who settled the bor- der villages of the municipality of [id for economical or political reasons, and migrants who came for personal reasons, i.e. marriage. In interviews, the following information was received: most people have no plans to return to the place from which they came; all of the interviewed people agreed that the border is characterised by great permeability, but they remember when there was no border. Most of the respon- dents, 73%, who found themselves in the border villages of the municipality of [id for economic or political 59 Tamara Luki}, Milka Bubalo - @ivkovi}, Bojan \er~an, Gordana Jovanovi}, Population Growth in the Border Villages of Srem, Serbia Table 6: Share of migrants according to the time of immigration, in total migrants (in %), according to the census 2002 in the border villages of the municipality of [id. Settlement Before 1940 1941–1945 1946–1960 1961–1970 1971–1980 1981–1990 1991–2002 Unknown Batrovci 0.0 0.0 23.6 13.4 7.1 7.1 47.2 1.6 Berkasovo 0.9 1.1 7.4 11.8 9.3 11.2 54.8 3.5 Biki} Do 1.1 2.2 11.8 5.1 12.4 14.0 51.1 2.2 Va{ica 1.3 0.3 8.3 4.9 3.9 7.9 71.9 1.5 Ilinci 1.1 1.4 18.3 12.0 12.9 8.3 44.1 1.7 Jamena 1.5 0.6 25.6 20.6 11.0 8.1 27.8 5.0 Ljuba 3.0 2.0 16.3 7.4 10.8 13.3 45.3 2.0 Molovin 1.6 1.6 6.3 17.2 17.2 12.5 43.0 0.8 Morovi} 0.7 0.5 12.9 11.2 8.8 9.1 55.5 1.2 Sot 0.5 0.2 5.1 3.2 4.9 6.7 77.0 2.3 Villages* 1.0 0.8 12.6 10.4 8.6 9.2 55.2 2.2 Town ([id) 0.9 0.9 11.8 16.6 14.4 11.5 38.5 5.4 Municipality** 1.0 0.9 11.4 12.6 10.3 9.8 50.2 3.9 Note: Villages* – 10 border villages of the municipality of [id; Municipality** – all (19) settlements of the municipality of [id; Source: Statistical Office of the Republic of Serbia, 2004b; own calculations. reasons said that they had adapted themselves to the environment in which they live and that while going back could be personally satisfying, it was not economically justifiable. They said if there were appropriate economic conditions, they would support (about 84%) the immigration of their children in directions further from the border. A small amount of respondents, about 12%, sees the border as a zone of connecting, and not dividing of people. Most, 92%, admit that there are the benefits to life next to the border. Most frequently they mention the prices of some products, which are lower on the other side of the border, and the profit they can make from selling different products to people from the Republic of Croatia. Similar phenomena have been determined in the other parts of the world (Fitzgerald et al. 1988; Timothy and Butler 1995; Sullivan and Kang 1997; Bygvra 1998; Wang 2004; Roper 2007). A positive migration balance for the period between 1991 and 2002 has been determined in half of the border villages of the municipality of [id, i.e. in all villages in which there was an increase of popu- lation and in the village of Sot (Table 7). The example of Sot confirms that settled population will not have the crucial importance for the development of the population in the future; this is confirmed by data received from research by Nikitovi} and Luki} (2010). The rate of migratory balance in border areas of Srem (15.1 ‰) is quite similar to the value in the entire municipality (14.1 ‰). At present, the settled population has only covered depopulation. Table 7: Migration balance of border villages of the municipality of [id in the period between 1991 and 2002. Settlement Population Average annual Migration Average annual Natural Average annual growth growth rate balance rate of migration population population growth (in ‰) balance (in ‰) growth rate (in ‰) Batrovci –38 –9.1 –24 24.5 –14 –33.6 Berkasovo 155 12.0 165 19.6 –10 –7.6 Biki} Do 37 10.7 39 15.5 –2 –4.8 Va{ica 122 6.6 132 11.7 –10 –5.1 Ilinci –40 –4.2 –26 10.3 –14 –14.5 Jamena –158 –10.8 –147 –3.5 –11 –7.3 Ljuba –22 –3.5 –17 3.9 –5 –7.4 Molovin –7 –2.1 –3 8.7 –4 –10.8 Morovi} 167 7.0 172 9.0 –5 –2.0 Sot –3 –0.3 11 15.0 –14 –15.3 Villages* 2559 15.1 2561 15.1 –2 0.0 Town ([id) 213 2.0 293 2.8 –80 –0.8 Municipality** 3938 9.4 4115 14.1 –177 –4.7 Note: Villages* – 10 border villages of the municipality of [id; Municipality** – all (19) settlements of the municipality of [id; Source: Statistical Office of the Republic of Serbia, 2004a; 2004b; 2010; own calculations 60 Acta geographica Slovenica, 54-1, 2014 3.3 Ethnic structure Ethnic minorities have been present in the municipality of [id for centuries. In Berkasovo, Ba~inci, a rural village in the municipality of [id that is not a border village and in the town of [id itself, the arrival of Rusyns was recorded in 1746 (\ur|ev 1998; Ivkov 2006, 45; Drlja~a 2006). At the end of the 18th centu- ry, the Diocese of Krièvci (Croatia) moved the Rusyns from the Ba~ka settlements of Ruski Krstur and Kucura (Gavrilovi} 1956, 70; 1958; 1977, 153–215; \er~an et al. 2010, 66). However, according to Beserminï (1937), Labo{ (1979, 299) and Rama~ (2009, 235), the Rusyns migrated from Krstur and Kucura, first to other settlements in Ba~ka and from the beginning of the 19th century to Srem and Slavonia, due to the troubles of the rural populace, which were caused by natural disasters, floods, drought and differ- ent field pests as well as due to the lack of arable land. According to Sirácky (2002), Slovaks resettled in Slavonia and Srem in 1770. Stupavský (2010) report- ed the presence of Slovaks in [id since 1810 and its existence within the military boundary with particular emphasis on the benefits of the town. According to Jankulov (1961), Slovaks inhabited the area in the mid- dle of the 19th century. As he writes, the first families immigrated from Slovakia and Hungary, and in the second half of the 19th century they immigrated from Ba~ka on a larger scale. At that time, the area was also settled by Jews. The colonisation of the Hungarians is miniscule compared to other parts of Vojvodina. A series of political developments, including changes in states' borders and the formation of new states, rendered Vojvodina a territory of migrations throughout the 20th century. These migrations have exert- ed a considerable impact upon Vojvodina's ethnic structure (Bjeljac and Luki}, 2008). Table 8: Ethnic structure of population in the border villages of the municipality of [id (in %), according to the 1991 and 2002 censuses. Ethnic group Serbs Slovaks Rusyns Croats Others Census 1991 2002 1991 2002 1991 2002 1991 2002 1991 2002 Batrovci 54.6 67.8 0.3 0.3 No data 1.3 38.3 28.4 6.8 2.2 Berkasovo 54.7 68.5 2.3 1.7 15.0 8.3 3.8 34.7 11.0 Biki} Do 14.4 32.7 1.3 2.1 47.6 13.0 11.6 71.2 6.0 Va{ica 63.9 86.2 2.4 1.4 0.8 25.7 7.2 7.9 4.4 Ilinci 93.3 96.3 0.2 0.4 0.0 2.3 1.0 4.2 2.4 Jamena 88.8 93.4 0.0 0.0 0.3 4.6 2.8 6.6 3.5 Ljuba 9.9 16.5 55.9 53.8 0.4 28.2 22.7 6.0 6.6 Molovin 84.3 87.6 0.0 0.3 0.3 8.5 4.7 7.2 7.0 Morovi} 61.9 87.3 0.5 0.4 0.3 28.4 8.0 9.3 4.1 Sot 4.4 43.0 4.2 3.5 0.9 57.6 40.1 33.8 12.5 Villages* 59.0 75.6 4.6 4.2 4.1 21.5 10.4 14.8 5.8 Town ([id) 63.5 76.2 6.9 5.5 4.2 8.8 4.4 20.8 9.7 Municipality** 59.7 77.6 7.8 6.5 3.4 16.7 5.4 15.8 7.2 Note: Villages* – 10 border villages of the municipality of [id; Municipality** – all (19) settlements of the municipality of [id; Source: Statistical Office of the Republic of Serbia, 2003; own calculations. In calculating the shares of certain ethnic groups in the total number of inhabitants of border villages of the municipality of [id, some of the information that was obtained by interviewing the population has been confirmed. According to the census from 2002, Serbs were the majority in eight out of ten observed villages. Rusyns were the majority in Biki} Do, but significant presence of them (15%) has also been deter- mined in Berkasovo. Slovaks were the majority only in Ljuba (Figure 4). In order to determine whether and to what extent population trends affected the ethnic structure, data from the last two censuses have been compared, according to which the share of Serbs has been increased in all villages. This contingent of refugees has directly increased the ethnic homogeneity of population (Matijevi} et al. 2005, 119). This supports the assertion of Cordeiro (1996) and Samers (1998, 124) that immigrants do not have to also be ethnic minorities. Data on Rusyns from 1991 were not published. The share of the Croats has decreased in all villages, in Morovi} and Va{ice by more than two thirds. According to their share in the entire population, in 1991 Figure 4: Dominant ethnicity in the border villages of the municipality of [id, according to the 1991 and 2002 censuses. p p. 62 61 Tamara Luki}, Milka Bubalo - @ivkovi}, Bojan \er~an, Gordana Jovanovi}, Population Growth in the Border Villages of Srem, Serbia AICV Y OR LIT IT M IPA A IC A K N Y S K U 1 N M M LIT 2 E LA RS IPA PAA IC 3 K N Č U Y AB M 4 LIT 5 6 IPA A IC D N N I N 7 U 4 V 1 M A O ID G 8 Š I A 2 E 0 1 N 1 S Z I A R O T 9 1 B E f Srem 1 H A ts o O en 2 R ača 0 C 3 0 o vo 1 2 o a a R vin vci vić a en sk lo ić D ci b ro er settlem izić t o o eštin o ik ersak ašica ju atro V rd L S M B B Šid N Ilin V B M Jam Srem o . . . . . . . . . . . . . . N B 1 2 3 4 5 6 7 8 9 0 1 2 3 4 1 1 1 1 1 AICV Y OR LIT IT M IPA A IC A K N K Y S U N 1 M M LIT 2 E LA R IPA S PAA ICN 3 KČ U Y AB M 4 LIT 5 6 IPA A IC D 19 N N I N 9 U 7 41 V 1 M A 3 O 0 ID 0 8 G m Š 2 I A k , 2 E S 0 1 0 N Z 1 3 S Z ; R I A R 10 T 9 1 O 1 E 0 B A H e, 2 ality O ić ind e village area k R u icip C ić jvo n o f th 3 k u 1 ara L u 5 f m 1 am ara L arta V aries o s s a k er o d ts: T am n n s : T rd u p vak syn ats ers ten rafsk o o wo u erb u ro th n ap g B B T ro S Slo R C O f co f m eo d ic g r o r o 8 n o o rce: G egen th th th u L u u E o 0 A A S 62 Acta geographica Slovenica, 54-1, 2014 the Croats were the majority in Sot (Table 8). In interviews, it was explained that in 1990s, during the wars on the territory of Former Yugoslav Republics, Croats from villages in the municipality of [id agreed to exchange their houses with Serbs from the territories of Croatia and Bosnia and Herzegovina. There is some mention of this by Kova~evi} et al (2010, 72). Moreover, it was reported that in some villages certain political parties acted repressively, thereby moti- vating the Croatian population to migrate. The proximity of the border, i.e. Croatian territory, was a powerful and attractive motive for the Croatian population to move to nearby villages on the other side of the bor- der; some of them already owned and cultivated land there. 4 Conclusion Different tendencies in population trends were observed in ten border villages of the municipality of [id in the period from the census in 1991 to the census in 2002. In four villages, there has been a determined increase in population. Analysing the local geography, it has been determined that those villages, unlike the others, are located either on busy roads or at crossroads. The more favourable position attracted peo- ple to settle those villages. Analysing natural population movement, it has appeared that from the four villages, only Biki} Do has positive population growth during half of the observed period. Accordingly, it has been concluded that the other villages had increased populations only as a result of a mechanical flow of population, which is confirmed by the fact that during the observed decade mass immigrations of people from the territories of former Yugoslavia to the region were taking place in the Federal Republic of Yugoslavia as a whole, and in the municipality of [id specifically. Interviewing the refugee population for the purpose of obtaining information on their intentions about further movement, the most com- mon answer received was that it depended on the economic situation. However, while visiting the field, the presence of different ethnic minorities was observed, which initiated analyses of data on ethnicity and the making of ethnic maps. The map confirmed that Biki} Do is the only village dominated by the Rusyn minority, which could also be one of the reasons only this border village has positive natural population growth. Drawing borders has positively affected the population numbers of border villages of the munic- ipality of [id, but the migration balance shows that a one-time špopulation dosage’ cannot obtain population growth in the conditions of negative trends observed at natural population movement. 5 Acknowledgments This paper is part of the project No. 114-451-2644/2012-01 funded by the Provincial Secretariat for Science and Technological Development of the Vojvodina Province, Serbia. The authors are grateful to the reviewers, whose comments and criticisms have ensured the quality of the paper. 6 References Beserminï, G. 1938: Naselьovanє Rusnacoh do [idu. Ruski kalendar 1937. Ruski Kerestur. Bjeljac, @., Luki}, V. 2008: Migrations on the territory of Vojvodina between 1919 and 1948. East European qarterly 42. Bogdanovi}, @., Tomi}, P., Romeli}, J., Plav{a, J., Lazi}, L., Kralj, \. 1997: Op{tina Ba~ka Palanka, geograf- ska monografija. Univerzitet u Novom Sadu, Prirodno-matemati~ki fakultet. Novi Sad. Bygvra, S. 1998: The road to the single European market as seen through the Danish retail trade: cross-bor- der shopping between Denmark and Germany. The International Review of Retail, Distribution and Consumer Research 8. London. DOI: http://dx.doi.org/10.1080/09593969800000003 Cordeiro, A. 1996: Usages et contre-usages des statistiques du chomage des immigres. Hommes et migra- tions 1204. ]upurdija, B. 1998: Izve{taj o stanju kolonizacije Bajmoka 1946. godine. Zbornik Matice srpske za istoriju 58. ]ur~i}, S. 2001: Naselja Srema – geografske karakteristike. Matica srpska. Novi Sad. 63 Tamara Luki}, Milka Bubalo - @ivkovi}, Bojan \er~an, Gordana Jovanovi}, Population Growth in the Border Villages of Srem, Serbia ]ur~i}, S., \uri~i}, J., Marjanovi}, V. 2002: Op{tina Sremska Mitrovica, geografska monografija. Univerzitet u Novom Sadu, Prirodno-matemati~ki fakultet. Novi Sad. \er~an, B., Bubalo - @ivkovi}, M., Luki}, T. 2010: Demografske promene u pograni~nim naseljima Srema na primeru Va{ice. Zbornik radova Geografskog fakulteta u Beogradu 58. Drlja~a, D. 2006: Rusnaci u etnoґrafskih zapisoh/Rusini u etnografskim zapisima. Dru{tvo za rusinski jezik, knjièvnost i kulturu. Novi Sad. \ur|ev, B, S. 1998: Geografija stanovni{tva. Institut za geografiju Prirodno-matemati~kog fakulteta. Novi Sad. \ur|ev, B., Arsenovi}, D., Dragin, A. 2010: Contemporary problems in studying population of Vojvodina Province. Acta geographica Slovenica 50-1. DOI: http://dx.doi.org/10.3986/AGS50105 \ur|ev, S., B., Martinov-Cvejin, M., Penev, G., Jovanovi}, S., Stevanovi}, R. 2004: Demografska situacja u Vojvodini poslednje decenije XX i po~etkom XXI veka. Zbornik Matice srpske za dru{tvene nauke 116–117. DOI: http://www.dx.doi.org/10.2298/ZMSDN0417199D Fitzgerald, J., D., Quinn, T., P., Whelan, B., J., Williams, J., A, 1988: An analysis of cross-border shopping. The economic and social research institute Dublin, General research paper 137. Ga}e{a, N. 1984: Agrarna reforma i kolonizacija u Jugoslaviji 1945–1948. Matica srpska – odelenje za dru{tvene nauke. Novi Sad. Gavrilovi}, S. 1956: Rusini u [idu od 1803–1848. Godi{njak Filozofskog fakulteta u Novom Sadu 1. Gavrilovi}, S. 1958: [id i {idsko vlastelinstvo (1699–1849). Zbornik Matice srpske za dru{tvene nauke 16–19. Gavrilovi}, S. 1977: Rusini u Ba~koj i Sremu od sredine XVIII do sredine XIX veka. Godi{njak Dru{tva istori~ara Vojvodine. Novi Sad. Geografska karta Vojvodine. 2001: AP Vojvodina 1 : 450.000. Smederevska Palanka. Hooghe, M., Trappers, A., Meuleman, B., Reeskens, T, 2008. Migration to European countries, A structural explanation of patterns, 1980–2004. International Migration Review 42-2. DOI: http:/ dx.doi.org/10.1111/ j.1747-7379.2008.00132.x Ivkov, A. 2006: Demografska slika Vojvodine. Zadùbina Andrejevi}. Beograd. Ivkov - Dìgurski A., Bubalo - @ivkovi}, M., Luki}, T., Dragin, A., Ivanovi}, Lj., Pa{i} M. 2010: Demografski razvoj pograni~nih op{tina Banata u drugoj polovini XX veka. Pokrajinski sekretarijat za nauku i tehno- lo{ki razvoj i Departman za geografiju, turizam i hotelijerstvo. Novi Sad. Jankulov, B. 1961: Pregled kolonizacije Vojvodine u XVIII i XIX veku. Novi Sad. Kova~evi}, T. 2006: Op{tina Subotica, geografska monografija. Univerzitet u Novom Sadu, PMF, Departman za geografiju, turizam i hotelijerstvo. Novi Sad. Kova~evi}, T., \ur|ev, B., Arsenovi} D. 2009: Movement of population in the Romanian border region, Case studing: Nova Crnja municipality. Geographica Timisiensis 18/1-2. Kova~evi}, T., Zaki}, L., Bubalo - @ivkovi}, M. 2010: Age-gender Structure of Croats in Vojvodina Province. Human geographies 4-2. Labo{, F. 1979: Istoriя Rusinoh Ba~keй, Srimu i Slavoniï 1745–1918. Lim, M., Metzler, R., Bar-Yam, Y. 2007: Global pattern formation and ethnic/cultural violence. Science 317. DOI: http://dx.doi.org/10.1126/science.1142734 Luki}, V, 2010: Population Dynamics and Commuting in Serbia. Spatial demography of the Balkans: trends and challenges, 4th International Conference of Balkans Demography. Budva. Luki}, V., Matijevi}, D. 2006: Op{tine u Vojvodini sa najve}im udelom izbeglica – uticaj na dinamiku i strukturne karakteristike populacije. Zbornik Matice srpske za dru{tvene nauke 121. Novi Sad. Luki}, V., Nikitovi}, V. 2004: Refugees from Bosnia and Herzegovina in Serbia: A Study of Refugee Selectivity. International Migration 42-4. DOI: http://dx.doi.org/10.1111/j.0020-7985.2004.00296.x Luki}, V., To{i}, B, 2011: Daily commuting – similarities and differences between Serbia and Slovenia. Acta geographica Slovenica, 51-2. DOI: http://dx.doi.org/10.3986/AGS51205 Machold, I., Dax, T., Meisinger, A. 2002: Youth participation in rural society in Maurau, Austria. In: T. Dax and I. I. Machold, Editors, Voices of Rural Youth: A break with traditional patterns? Wien. Matijevi}, D, To{i}, B, Luki}, V. 2005: Uticaj migracija na populacione i funkcionalne promene sremskih op{tina. Glasnik Srpskog geografskog dru{tva 85-1. Meuleman, B., Davidov, E., Billet, J. 2009: Changing attitudes toward immigration in Europe, 2002–2007: A dynamic group conflict theory approach. Social science research 38-2. DOI: http://dx.doi.org/10.1016/ j.ssresearch.2008.09.006 64 Acta geographica Slovenica, 54-1, 2014 Nikitovi}, V., Luki}, V. 2010: Could Refugees Have a Significant Impact on the Future Demographic Change of Serbia? International Migration 48-1. DOI: http://dx.doi.org/10.1111/j.1468-2435.2009.00519.x Ni Laoire, C. 2000: Conceptualising Irish rural youth migration: a biographical approach. International Journal of Population Geography 6. O'Docherty Madrayo, L. 1988: The Hidden Face of The War in Central America. The sociology of involon- tary migration. Current sociology 36-2. Penev, G. 1994: Demografska situacija u pograni~nim naseljima Srbije. Stanovni{tvo 32/3-4. Pilkington, H. 1998: Migration. Displacement, and Identity in Post-Soviet Russia. London. Rama~, J. 2009: Slavko Gavrilovi} u istoriografiji o Rusinima u Jùnoj Ugarskoj. Istraìvanja 20. Roper, S. 2007: Cross-border and local co-operation on the island of Ireland: An economic perspective. Political geography 26. DOI: http://dx.doi.org/10.1016/j.polgeo.2007.04.002 Samers, M. 1998: Immigration, šethnic minorities’, and šsocial exclusion’ in the European Union: a critical perspective. Geoforum 29-2. Sirácky, J. 2002: Dlhé hľadanie domova. Martin. Stankovi}, V. 2006: Op{te i metodolo{ke informacije o popisu. Stanovni{tvo i doma}instva Srbije prema popisu 2002. godine. Beograd. Statistical Office of the Republic of Serbia. 2003: Stanovni{tvo, Popis stanovni{tva, doma}instva i stanova u 2002, Nacionalna ili etni~ka pripadnost, 1. Republi~ki zavod za statistiku. Beograd. Statistical Office of the Republic of Serbia. 2004a: Stanovni{tvo, Popis stanovni{tva, doma}instva i stano- va u 2002, Uporedni pregled broja stanovnika – 1948, 1953, 1961, 1971, 1981, 1991 i 2002, podaci po naseljima, 9. Republi~ki zavod za statistiku. Beograd. Statistical Office of the Republic of Serbia. 2004b: Stanovni{tvo, Popis stanovni{tva, doma}instva i stanova u 2002, Migraciona obelèja, podaci po naseljima, 8. Republi~ki zavod za statistiku. Beograd. Statistical Office of the Republic of Serbia. 2010: Broj ro|enih i umrlih, po godinama, za period 1989–2002. Interna dokumentacija. Novi Sad. Stockdale, A. 2002: Towards a typology of out-migration from peripheral areas: a Scottish Case Study. International journal of population geography 8. DOI: http://dx.doi.org/10.1002/ijpg.265 Stockdale, A. 2006: Migration: Pre-requisite for rural economic regeneration? Journal of Rural Studies 22-3. DOI: http://dx.doi.org/10.1016/j.jrurstud.2005.11.001 Stupavský, S. 2010: Slováci v [íde 1810–2010. Matice slovenská v Srbsku. Bá~sky Petrovec. Sullivan, P.M, Kang, J, 1997: Information sources and motivational attributes of Canadian cross-border shoppers: a pilot study. International journal of commerce and management 7-1. Timothy, D., J., Butler, R., W, 1995: Cross-border shopping – a North-American perspective. Annals of tourism research 22-1. VGI. 1982: Topografska karta 1 : 50.000 Ba~ka Palanka 377-3. Beograd. VGI. 1982a: Topografska karta 1 : 50.000 Bijeljina 427-1. Beograd. VGI. 1982b: Topografska karta 1 : 50.000 Bijeljina 427-2. Beograd VGI. 1983: Topografska karta 1 : 50.000 Ba~ka Palanka 377-4. Beograd. Vrecer, N. 2010: Living in Limbo: Integration of Forced Migrants from Bosnia and Herzegovina in Slovenia. Journal of refugee studies 23-4. DOI: http://dx.doi.org/10.1093/jrs/feq042 Vujadinovi}, S., Pavlovi}, M., [abi}, D. 2010: Integralni odrìvi razvoj na primeru lokalne geografske sre- dine. Glasnik Srpskog geografskog dru{p{tva XC-2. Beograd. Wang, D. 2004: Hong Kongers'cross-border consumption and shopping in Shenzhen: patterns and moti- vations. Journal of retailing and consumer services 11. DOI: http:/ dx.doi.org/10.1016/S0969-6989(03)00014-6 65 66 Acta geographica Slovenica, 54-1, 2014, 67–87 THE WELLBEING OF SLOVENIA'S POPULATION BY REGION: COMPARISON OF INDICATORS WITH AN EMPHASIS ON HEALTH BLAGINJA PREBIVALCEV SLOVENIJE PO REGIJAH: PRIMERJAVA KAZALNIKOV S POUDARKOM NA ZDRAVJU Lilijana [prah, Tatjana Novak, Jerneja Fridl Wellbeing is an abstract, multidimensional, and complex concept that includes not only components of the subjective experience of happiness, satisfaction, and prosperity, but also objectively measurable indicators, and so it can be only measured indirectly (Artist: Metod Frlic, academic sculptor. Untitled (2008). Painting on plywood, acrylic, 158 cm × 202 cm). Blaginja je abstrakten, ve~razseèn in kompleksen pojem, ki vklju~uje tako komponente subjektivnega doìvljanja sre~e, zadovoljstva in prosperitete, kakor tudi objektivno merljive kazalnike, zato jo lahko merimo le posredno (Avtor: Metod Frlic, akademski kipar. Brez naslova (2008). Slika na vezani plo{~i, akril, 158 cm × 202 cm). Lilijana [prah, Tatjana Novak, Jerneja Fridl, The wellbeing of Slovenia's population by region: comparison of indicators with … The wellbeing of Slovenia's population by region: comparison of indicators with an emphasis on health DOI: http://dx.doi.org/10.3986/AGS54104 UDC: 913:330.59(497.4) 330.59:613(497.4) COBISS: 1.01 ABSTRACT: In broader definitions, wellbeing is commonly described as a multidimensional concept, defined by the state of happiness, health, and prosperity. However, due to various understandings of conceptual issues regarding wellbeing, professionals encounter a number of methodological problems connected with measuring it. Composite indicators are thus being increasingly used to measure population's wellbeing. Health is an important area of wellbeing and is connected with indicators similar to those used for mea- suring general wellbeing. This article uses composite indicators to compare various areas of wellbeing, and especially health-related wellbeing, among the twelve Slovenian statistical regions. The findings show great differences between Slovenian regions. In western Slovenia (the Central Slovenia, So~a, Coastal-Karst, and Upper Carniola regions), the level of wellbeing is generally high, and in eastern Slovenia (the Carinthia, Lower Sava, Mura, and Central Sava regions) it is lower. Except for minor deviations, the level of gener- al wellbeing in the regions matches the level of health-related wellbeing. KEYWORDS: geography, medicine, population's wellbeing, composite wellbeing indicator, health, region, mental disorder The article was submitted to the editorial board on September 13, 2012. ADDRESSES: Lilijana [prah, Ph. D. Sociomedical Institute Scientific Research Centre of the Slovenian Academy of Sciences and Arts Novi trg 2, SI – 1000 Ljubljana, Slovenia E-mail: lilijana.sprahazrc-sazu.si Tatjana Novak Sociomedical Institute Scientific Research Centre of the Slovenian Academy of Sciences and Arts Novi trg 2, SI – 1000 Ljubljana, Slovenia E-mail: tnovakazrc-sazu.si Jerneja Fridl, M. Sc. Anton Melik Geographical Institute Scientific Research Centre of the Slovenian Academy of Sciences and Arts Gosposka ulica 13, SI – 1000 Ljubljana, Slovenia E-mail: jernejaazrc-sazu.si 68 Acta geographica Slovenica, 54-1, 2014 1 Introduction An overview of the literature on conceptual issues of wellbeing and its measurements reveals many method- ological problems (Matthews 2006; Costanza et al. 2009). Wellbeing is a complex concept, defined as a state of happiness, health, and prosperity (Cowie and Lewis 1989, 1450). Due to its abstract and multidimen- sional nature, it can only be measured indirectly using a series of selected indicators, which must also be appropriately contextualized within a specific economic, social, and cultural environment, and primar- ily include those social values that reflect the perception of wellbeing in a specific environment. Recently, there has been increased interest among the professional and research community in studying wellbeing as well as many discussions on suitable methodological approaches to measuring it (Matthews 2006). In this regard, the main question is whether wealth and economic development are crucial to defining well- being. Ever since the establishment of the Organization for Economic Cooperation and Development (OECD) in 1961, the gross domestic product (GDP) has been the main indicator of measuring and understanding economic and social progress, which has also been connected with wellbeing. However, current studies point to a multilayered nature of the concept of wellbeing, which also includes subjective and nonmaterial com- ponents such as happiness, satisfaction, freedom, health, and education (Diener and Seligman 2004; Costanza et al. 2009). The OECD has also responded to some methodological and content-related problems connected with measuring wellbeing. On its fiftieth anniversary, as part of the project »OECD Wellbeing Indicators« (OECD 2011), it presented a new method of monitoring general wellbeing as a response to demands for comparative information on the living conditions of people in countries with varying levels of develop- ment. The OECD wellbeing indicators include indicators of material conditions (income and wealth, jobs and housing), and quality of life (health, work-life balance, education, community, civil engagement and government, quality of the environment, safety, and life satisfaction; OECD 2011, 18, 19). The majority of indicators are based on statistical data, but some are also developed based on opinion polls. The current financial and economic crisis opens numerous new aspects of understanding wellbeing, also in connection with the current global and social challenges related to climate changes, demograph- ic trends, and public health (Stuckler et al. 2009). Evidence suggests that economic development is not necessarily connected with better wellbeing (Boarini, Johansson and D'Ercole 2006; Mikuli}, Sándor and Leoncikas 2012). Especially topical is the question of how the crisis will be reflected in people's health. The findings show that during crises specific diseases and death rates increase due to distinctive reasons (e.g., sui- cide rate), mental health deteriorates (more depression and anxiety disorders), and the rates of domestic violence and other violence increase, as does drug and alcohol abuse (Levy & Sidel 2009; Av~in et al. 2011; Stuckler et al. 2011). Alarming is also the prediction that the crisis will increase inequalities in health, which will result in a lower level of wellbeing in a number of population groups (Buzeti et al. 2011; Gabrijel~i~ Blenku{ et al. 2012). Improving population's wellbeing is one of the main development goals of any country, and there- fore Slovenia also included this in Slovenia's Development Strategy (2005). Even when an individual country as a whole shows a fairly high level of wellbeing at an international scale, there can be considerable dif- ferences between individual areas or regions within the country. Regional differences in wellbeing can result from social, economic, and environmental problems that hinder balanced social and regional develop- ment. Therefore it is vital to continually monitor the geographically dependent levels of wellbeing, especially as they relate to effectively planning and implementing measures as part of spatial, economic, and health- care policies, and ensuring access to public services, work, and high-quality living conditions (Rovan, Male{i~ and Bregar 2009, 71; Kerbler 2012, 175–176). 2 Purpose of the study and description of methodology The aim of the present study is to explore the general wellbeing in individual statistical regions of Slovenia, and analyze the differences between them in terms of various aspects of wellbeing and selected health-relat- ed indicators. Even though in recent years methodologies using composite indicators have become increasingly estab- lished in measuring wellbeing (OECD 2008), no »super« indicator is currently available that could be 69 Lilijana [prah, Tatjana Novak, Jerneja Fridl, The wellbeing of Slovenia's population by region: comparison of indicators with … regarded as an official wellbeing measure. Therefore, based on the available statistical data and taking into account the methodology recommended by the OECD (2008, 2011), composite wellbeing indicators (CWBI) were developed for the purposes of this study. There are several regionalizations or divisions of Slovenia in place (Perko 1998), but for this study the division into statistical regions proved to be the most appro- priate. 2.1 Selection criteria for basic indicators of wellbeing In selecting the basic sociodemographic, economic, healthcare, and environmental indicators for the CWBI, the conceptual adequacy of indicators, their availability in statistical regions, accessibility during the ref- erence period (2006–2010), quality, and capacity to sum up several features of the phenomenon (expressed in the form of indexes, ratios, and coefficients) were taken into account. The following secondary sources of statistical data were used: 1. SI-STAT online information portal of the Statistical Office of the Republic of Slovenia /SURS/ (Internet 1); 2. Electronic publications of the Slovenske regije v {tevilkah (Slovenian Regions in Numbers) from 2006 to 2010 (SURS 2006–2010); 3. Zdravstveni statisti~ni letopis (Health Statistics Yearbook), 2006–2008 (IVZ 2006–2008); 4. Statistical appendices to the publication of the Institute of Macroeconomic Analysis and Development /UMAR/ (Apohal Vu~kovi~ et al. 2010, 127). 3 Identification of regional wellbeing on the basis of composite wellbeing indicators 3.1 Structure of a composite indicator of wellbeing The CWBI areas and dimensions were identified based on the areas of the OECD indicators of wellbe- ing (OECD 2011). The CWBI of every region includes seventy basic indicators that were divided into sixteen areas (dimensions) of wellbeing: income, education, housing, jobs, environment, general health, safety, parental benefits, social transfers, availability of health and social services, risk behaviors, occupational health, neonatal health, stability of partnerships, developmental prospects, and demographic profile. The number of basic indicators included differs across dimensions, as indicated by the values provided in parentheses in Figure 1. Before the development of the composite indicator, the statistical data of basic indicators that were not expressed as ratios (percentages, coefficients, and indexes) were recalculated into comparable units (per population and area of region) and standardized. A multivariate principal component analysis, which aims to reduce the scope of data or, in our case, indicators, while losing as little information as possible, was then used to develop a composite wellbeing indicator from a selection of basic indicators. Basic indi- cators were retained in an individual dimension only if they had relevant content for a particular area of wellbeing and if, based on the results of the principal component analysis, they explained the highest pos- sible variance of data behind the basic indicators making up this component. The numerical value of an individual dimension was calculated by multiplying basic indicators by component weights and then the results obtained were averaged across the time period studied. A linear transformation of a STEN score, a standard scale running from 1 to 10, was used to classify regions according to their wellbeing levels in particular areas. A value of 1 represented the lowest calculated value pertaining to a particular dimen- sion of wellbeing (the lowest level of wellbeing in a particular area), whereas a value of 10 was assigned to the highest calculated value of dimension of wellbeing (the highest level of wellbeing in a particular area). The CWBI value was calculated as a mean value of all sixteen dimensions of wellbeing within a par- ticular statistical region. Regions were classified according to their CWBI values into four categories: regions of high wellbeing, regions of moderately high wellbeing, regions of moderately low wellbeing, and regions of low wellbeing. Table 1 shows basic indicators included in the dimensions of wellbeing and their influence on well- being. The plus sign was assigned to indicators when their high values (e.g., working population) contributed 70 Acta geographica Slovenica, 54-1, 2014 DEVELOPMENTAL PROSPECTS/ RAZVOJNE MOŽNOSTI (1) DEMOGRAPHIC PROFILE/ DEMOGRAFSKI EDUCATION/ PROFIL IZOBRAZBA HOUSING/ STABILITY OF (7) (5) STANOVANJSKE PARTNERSHIPS/ RAZMERE STABILNOST (2) PARTNERSKIH ZVEZ (1) INCOME/ NEONATAL HEALTH/ DOHODEK PERINATALNO ZDRAVJE (3) (3) JOBS/ OCCUPATIONAL ZAPOSLENOST HEALTH/ (8) POKLICNO ZDRAVJE (6) A COMPOSITE WELLBEING INDICATOR (CWBI)/ SESTAVLJEN KAZALNIK BLAGINJE (SKB) ENVIRONMENT/ RISK BEHAVIORS/ OKOLJE TVEGANA VEDENJA (3) (6) AVAILABILITY OF HEALTH GENERAL HEALTH/ AND SOCIAL SERVICES/ SPLOŠNO ZDRAVJE RAZPOLOŽLJIVOST (10) ZDRAVSTVENIH IN SOCIALNIH SLUŽB (4) SAFETY/ VARNOST (5) SOCIAL TRANSFERS/ SOCIALNI TRANSFERJI (2) PARENTAL BENEFITS/ STARŠEVSKO VARSTVO (4) Figure 1: Structure of a regional composite wellbeing indicator in terms of wellbeing dimensions and the number of basic indicators included in them. to a higher level of wellbeing within a region. The minus sign stands before indicators whose higher val- ues (e.g., unemployment rate) signal lower levels of wellbeing in the region. A shorter time period (three or four years) was taken into account regarding those indicators that were not available for the full ref- erence time period (2006–2010). 3.2 Inter-regional comparison with respect to different levels and areas of wellbeing Figure 2 compares social, demographic, health, economic, and environmental dimensions of wellbeing between statistical regions of Slovenia. The regions were divided into four groups in terms of their CWBI 71 Lilijana [prah, Tatjana Novak, Jerneja Fridl, The wellbeing of Slovenia's population by region: comparison of indicators with … Table1: Overview of basic wellbeing indicators comprising the composite indicator of wellbeing and their influence on wellbeing. DERIVED BASIC INDICATOR INFLUENCE DATA SOURCE AND INDICATOR ON WELL-BEING REFERENCE PERIOD Income GDP per capitaa index + SURS, 2006–2008 GDP per capita in purchasing power standard units index + SURS, 2006–2008 Net monthly salary of an employed person + SURS, 2006–2010 Education Share of population 22 – 64 years of age with no education, with an incomplete education, or primary education – SURS, 2006–2009 Share of population 22 – 64 years of age with secondary education + SURS, 2006–2009 Share of population 22 – 64 years of age with tertiary education + SURS, 2006–2009 Proportion of student population within the actively working population + SURS, 2006–2009 Share of adult population 22 – 64 years of age engaged in lifelong learning + SURS, 2006–2009 Housing Average household floor space (m2) per person + SURS, 2006–2010 Number of completed dwellings (new constructions, additions, changes in intended use) + SURS, 2006–2010 Jobs Share of actively working population + SURS, 2006–2010 Employment-population ratio + SURS, 2006–2009 Registered unemployment rate – SURS, 2006–2010 Share of unemployed with primary education – SURS, 2006–2010 Share of unemployed with secondary or tertiary education – SURS, 2006–2010 Job vacancies + SURS, 2006–2010 Share of employed persons 55 – 64 years of age + SURS, 2007–2009 Number of active enterprises + SURS, 2006–2009 Environment Annual volume of water supplied to households from public water supply + SURS, 2006–2010 Discharge of unpurified wastewater from public sewage system – SURS, 2007–2009 Estimated damage caused by natural disasters as percentages of regional GDP – SURS, 2006–2008 General health Number of drug prescriptions per person – IVZ, 2007–2009 Rate of hospital treatment of diseases – IVZ, 2006–2009 Number of cases with circulatory diseases as the most frequent causes of death – IVZ, 2006–2009 Number of cases with digestive diseases as the most frequent causes of death – IVZ, 2006–2009 Number of visits in general practice for endocrine, metabolic, and eating disorders – IVZ, 2006–2008 Number of visits in general practice for mental and behavioral disorders – IVZ, 2006–2009 Number of visits in general practice for circulatory disorders – IVZ, 2006–2008 Number of visits in general practice for metabolic and eating disorders – IVZ, 2006–2008 Number of visits in general practice for musculo-skeletal disorders – IVZ, 2006–2008 Safety Total number of convicted adults – SURS, 2006–2010 Number of convicted adults by criminal offense against spouses, family, and children – SURS, 2006–2010 Total number of convicted minors (under the age of 18) – SURS, 2006–2010 Number of cases of self-harm – SURS, 2006–2009 Number of cases of assault on other persons – SURS, 2006–2009 Parental benefits Number of children 1 – 5 years of age in preschools + SURS, 2006–2009 Number of beneficiaries with the right to part-time work because of parenting duties + SURS, 2006–2009 Number of beneficiaries with the right to paternity leave compensation + SURS, 2006–2009 Number of marriages + SURS, 2006–2010 Social transfers Number of recipients of financial social assistance – SURS, 2006–2009 Number of recipients of scholarships among upper secondary and tertiary students + SURS, 2008–2010 Availability Number of physicians + SURS,2007–2009 of health Number of nurses + SURS,2007–2009 and social Number of hospital beds + SURS, 2007–2009 services Number of beds available in retirement homes + SURS, 2006–2009 Risk behaviors Number of persons seriously injured in traffic accidents – SURS,2006–2009 Number of persons killed in traffic accidents – SURS, 2007–2009 Hospitalization rates due to suicide – IVZ, 2006–2009 Number of suicides – IVZ, 2006–2009 Number of visits due to alcohol consumption – IVZ, 2006–2009 Number of drug abuse cases in primary care – IVZ, 2006–2009 72 Acta geographica Slovenica, 54-1, 2014 Occupational Number of reported injuries at work – IVZ, 2006–2009 health Share of work days lost due to sick leave per person – IVZ, 2006–2010 Frequency index (IF) b – IVZ,2006–2010 Seriousness of sick leave c – IVZ, 2006–2010 Rate of hospital treatment of diseases – IVZ, 2006–2009 Average duration of hospitalization due to illness – IVZ, 2006–2009 Neonatal health Stillbirths – IVZ, 2007–2009 Number of women giving birth via caesarian section – IVZ, 2006–2009 Share of newborns with low birth weight (under 2500 g) – IVZ, 2007–2009 Stability Number of divorces – SURS, 2006–2010 of partnerships Developmental Development hazard index d – UMAR, 2007–2013 prospects Demographic Population density – SURS, 2006–2009 profile Number of live births + SURS, 2006–2010 Number of deaths – SURS, 2006–2010 Total increase in population (natural and migration increase) + SURS, 2006–2010 Coefficient of age dependency e – SURS, 2006–2010 Aging index f – SURS, 2006–2010 Number of farmers within actively working population – SURS, 2006–2010 Notes: a The GDP per inhabitant index compares the GDP per inhabitant with the national GDP within the same year. b The Frequency index describes the number of sick leaves per 100 employees in one year. c Seriousness of sick leave signals the average duration of one sick leave due to illness, injury, or other medical reason. d The Development hazard index comprises eleven indicators (development, regional burden, and developmental prospects; Pe~ar & Kava{ 2006). e The Coefficient of age dependency is the ratio between the young (0–14 years), old (over 65 years), and work-capable (over 15 years) population. f The Aging index shows the ratio between the old (over 65 years) and young population (0–14 years), multiplied by 100. Definitions a and d–f are taken from data sources (Internet 1), whereas definitions b–c are taken from the Health Statistics Yearbook (IVZ 2006d). value (the values ranged from 7.6 to 3.3; interval: 1.07) and are represented in various shades of orange in the figure: • Group 1: Regions of high wellbeing (CWBI = 7.6 to 6.52): Central Slovenia region / Osrednjeslovenska regija/ (CWBI = 7.58). • Group 2: Regions of moderately high wellbeing (CWBI = 6.53 to 5.45): So~a region / Gori{ka regija/ (CWBI = 5.94), Coastal-Karst region / Obalno-kra{ka regija/ (CWBI = 5.90), Upper Carniola region / Gorenjska regija/ (CWBI=5.78), and Inner Carniola–Karst region / Notranjsko-kra{ka regija/ (CWBI=5.20). • Group 3: Regions of moderately low wellbeing (CWBI = 5.46 to 4.38): Savinja region / Savinjska regija/ (CWBI = 4.91), Southeast Slovenia / Jugovzhodna Slovenija/ (CWBI = 4.88), and Drava region / Podravska regija/ (CWBI = 4.75). • Group 4: Regions of low wellbeing (CWBI = 4.39 to 3.32): Carinthia region / Koro{ka regija/ (CWBI = 4.21), Lower Sava region / Spodnjeposavska regija/ (CWBI = 4.04), Mura region / Pomurska regija/ (CWBI = 3.45), and Central Sava region / Zasavska regija/ (CWBI = 3.37). There were considerable differences in wellbeing among the regions, with Central Slovenia standing out as the region with the highest level of wellbeing, and the Mura and Central Sava regions as having the lowest levels of general wellbeing (Figure 2). In western Slovenia there is a group of regions with rel- atively high levels of general wellbeing (the Central Slovenia, So~a, Coastal-Karst, and Upper Carniola regions), and in eastern Slovenia there is a group of regions with the lowest levels of general wellbeing (the Drava, Carinthia, Lower Sava, Central Sava, and Mura regions). Regions with higher levels of general wellbeing also exhibit high levels of wellbeing in all other areas. The residents of these regions have higher education profiles and higher incomes, experience better housing and environmental conditions, and also have more employment opportunities and better parental benefit opportunities. At the same time, these regions have better development opportunities and a more favorable demographic profile. Figure 2: Inter-regional comparison with respect to different levels and areas of wellbeing. p p. 74 73 Lilijana [prah, Tatjana Novak, Jerneja Fridl, The wellbeing of Slovenia's population by region: comparison of indicators with … , 2012ZU ožnosti SA /N IJAG IO E enzije blaginje ere elika ZRC G R ografski profil E A R K im A S R R U U ntona M M MOP Jerneja Fridl titut A ensions/ D ent/ okolje ental prospects/ razvojne m ovak, e/ dohodek ographic profile/ dem eografski inš /N IJAG ousing/ stanovanjske razm eneral health/ splošno zdravje ccupational health/ poklicno zdravje eonatal health/ perinatalno zdravje evelopm em IO E Incom Education/ izobrazba H Jobs/ zaposlenost Environm G Safety/ varnost Parental benefits/ starševsko varstvo Social transfers/ socialni transferji Availability of health and social services/ razpoložljivost zdravstvenih in socialnih služb Risk behaviors/ tvegana vedenja O N Stability of partnerships/ stabilnost partnerskih zvez D D G R E A R ellbeing dim R K A S Šprah, Tatjana N W M AVA AV R R D D Z, U OP RS, IV edicinski inštitut in G erilo: 1 : 850.000 ružbenom / D N A Scale/m Authors/avtorice: Lilijana Source/vir: SU © IO K G S / E N R AVS IO O IJA G IJA AVA P G E E R G S JE R E R N R E D AVA A W O K P SL S LO S / A AVS IA IJA TR N N N ZA E EV / E V N IJA C LO /N IO G LO S G E A IO IJA E R T S N G G R A S D E E K AE O R R JA ZH IA A IN JS TH K IN U V TH Š AV O O O S AV G IN R S S JU RA O C K /NIO AG T E KS S A R K / R N A Š N IA EV –K AR IO N / G E LO IJA LA N -K erno visoke blaginje E IJA V S G IO O IJA erno nizke blaginje R G E IO K E LO JE N G G S N R R E JS E LA R L D A R N R IO A A E C A N K R R aven blaginje v regijah R JS TR S E TR A N N O O E N N C E C IN R R km E O P G 50 PU elbeing/ regije zm elbeing/ regije zm w 40 /N IJA IO G G E E R / elbeing/ regije nizke blaginje elbeing/ regije visoke blaginje R A N 30 A K IJA w Č IŠ IO G oderately low oderately high w O R G E S O E R G ellbeing across regions/R T R A S K 20 R Š A AR L-K -KO TAS LN A A Regions of low Regions of m Regions of m Regions of high w 10 O B C O 5 The level of w 0 74 Acta geographica Slovenica, 54-1, 2014 3.3 Inter-regional comparison with respect to basic indicators of health-related wellbeing A comparison of regions in terms of the level of wellbeing in health-related areas showed that regions of high and moderately high wellbeing also display a generally higher level in general, occupational, and neona- tal health and the availability of health and social care services (comparing columns in Figure 2; higher CWBI values in Table 2). This was followed by an analysis of how certain selected indicators of health-relat- ed wellbeing are distributed across regions. Because health-related wellbeing can also be linked with drug and alcohol consumption, suicidal behavior, and injuries in car accidents, indicators making up the dimen- sion of »risk behaviors« were also included (Table 2). Table 2 shows that the general level of wellbeing does not necessarily reflect the wellbeing in individual areas within a specific region. Thus the Central Slovenia region (a region of high wellbeing in terms of its CWBI value) ranks high on the majority of basic indicators of wellbeing, but compared to other regions it exhibits some deviations in health-related areas such as the highest level of hospitalization due to dis- ease, a fairly high share of newborns with a low birth weight, a large number of treatments for drug abuse, and a large number of persons injured in car accidents. Such deviations can also be observed in other regions. In the Central Sava region (which has the lowest level of general wellbeing), a low level of health-related wellbeing predominates, but the region stands out with relatively good status in some other areas, such as the largest number of primary healthcare appointments due to musculo-skeletal disorders and a small number of injured in car accidents, fewer stillborn babies, and a relatively good availability of beds in retire- ment homes. 4 Discussion Until recently, wellbeing was predominantly measured with approaches that used either macroeconom- ic statistics such as the GDP or people's subjective opinions about their satisfaction with the quality of life as an approximation for the wellbeing assessment. It turned out that subjective opinions of wellbe- ing as part of international and interregional comparisons are not reliable because they depend strongly on the cultural context and various psychological factors (Diener 2000). Therefore, the use of compos- ite indicators is becoming increasingly established in measuring wellbeing (Matthews 2006; OECD 2011); this method was also used in the study presented here. Slovenia is treated as a homogenous regional unit in international comparisons, but many Slovenian economic, sociological, anthropological, and healthcare studies show great differences and special features at the level of its territorial units (municipalities and statistical regions), which are consequently reflect- ed in access to services, commodities, and infrastructure, in economic and employment opportunities, in the accessibility and availability of healthcare and social services, and elsewhere (Nared 2002; Bole 2004; Ravbar, Bole and Nared 2005; Nared 2007; Bole 2008a, Bole 2008b; Dernov{ek and [prah 2008; Bole 2011; Ravbar 2011; Kneèvi} Ho~evar 2012; Koreni~ and Mavec 2012). In various international studies, these differences and special features in Slovenia remain unnoticed because the data are aggregated at the nation- al level. This can also be seen from the findings of an OECD study (2011), in which interactive tools for measuring wellbeing were used to compare wellbeing across the OECD member states. Among the thir- ty-four members, Slovenia was ranked twenty-first overall. In some dimensions of wellbeing, it came close to the OECD average (health, social inclusion), or even higher (employment, personal safety); it fell below the OECD average with regard to housing and life satisfaction (Internet 2). This study focused on the level of wellbeing in Slovenian statistical regions as measured by the adapt- ed methodology of the OECD indicators. The results showed that, in terms of general wellbeing defined with a mean CWBI value, regions differ greatly from one another because the range of the CWBI was con- siderable: from 7.58 to 3.37. The situation in health-related wellbeing is especially interesting because in some regions it deviates from the general wellbeing status. That the estimated general wellbeing and health-related wellbeing match is also confirmed by the fact that a high level of wellbeing coincides with economically and socially better developed urban centers; however, a mismatch of these estimates in some regions also draws attention to the fact that favorable living and environmental conditions in municipalities do not necessarily reflect high economic and social development (Male{i~, Bregar, and Rovan 2009, 47, 51). 75 Lilijana [prah, Tatjana Novak, Jerneja Fridl, The wellbeing of Slovenia's population by region: comparison of indicators with … 0 0 7 N .9 .7 .6 .3 .7 .3 .0 .3 .6 .7 .1 .7 .8 .2 .1 .4 .0 .5 .7 .2 .1 .7 .9 .5 .4 .0 C 0 8 9 7 1 0 0 5 2 1 9 8 6 3 5 6 0 2 1 0 2 6 9 3 4 0 7 4 4 5 8 3 6 3 4 3 1 6 2 6 1 1 1 0 1 3 ;n U .1 .1 .7 .4 .8 .6 .8 .7 .7 .5 .9 .2 .6 .3 .3 .4 .4 .2 .7 .1 .6 .9 .5 .8 .1 .0 io M g 1 9 5 6 3 3 2 4 4 2 5 7 3 6 5 6 3 5 1 0 2 1 8 5 6 4 7 7 6 5 3 2 7 2 6 3 2 1 8 3 3 g in 1 2 1 re w e ja oL llb in e 4 9 1 va O w .2 .6 .0 .3 .6 .1 .6 .0 .0 .6 .5 .9 .2 .7 .4 .7 .9 .1 .9 .9 .5 .3 .6 .4 .1 .3 S L 4 8 5 7 8 5 6 4 8 7 5 7 3 6 5 6 3 4 0 0 2 3 6 3 3 4 8 4 4 3 9 2 8 1 4 3 1 5 1 5 – 1 1 1 A ; S 9 1 2 nio A .7 .9 .7 .3 .8 .6 .1 .6 .7 .9 .3 .2 .6 .9 .4 .9 .0 .4 .7 .4 .7 .9 .4 .5 .1 .0 g C 3 7 1 5 7 2 5 4 6 2 1 6 3 5 4 6 3 4 1 0 2 7 4 5 9 3 8 4 5 4 4 3 7 2 5 2 1 8 4 5 1 2 1 t rersaK 3 6 1 –la R .7 .6 .7 .9 .9 .3 .0 .3 .7 .3 .8 .2 .6 .5 .0 .3 .2 .2 .7 .2 .3 .9 .8 .4 .3 .3 io D 4 8 0 5 5 4 9 4 2 9 0 8 2 6 5 7 5 5 1 0 2 3 4 6 2 1 5 0 3 4 1 2 8 1 3 2 2 8 5 4 rna g 1 2 1 ly in r Ce te e 4 3 2 n E ra llb .3 .7 .4 .6 .8 .5 .9 .5 .3 .6 .3 .0 .5 .9 .4 .8 .4 .2 .3 .0 .3 .6 .8 .5 .1 .3 In S e e 5 7 8 1 6 4 1 4 4 9 8 8 2 8 4 6 5 5 1 0 2 4 6 4 8 7 6 0 d 2 4 9 3 8 1 2 2 1 6 2 5 – o w 1 1 1 M w ; IN lo n 4 5 5 iog A .2 .1 .6 .6 .2 .7 .9 .5 .6 .2 .4 .5 .2 .7 .3 .0 .3 .3 .7 .4 .8 .6 .6 .8 .0 .5 S 5 8 6 9 3 2 6 4 6 2 6 7 4 5 4 5 4 6 1 0 2 6 6 5 8 2 5 6 re 4 3 2 3 7 2 4 2 1 7 4 4 1 2 1 laiorn 3 0 9 a .7 .9 .2 .5 .6 .9 .6 .2 .2 .8 .9 .6 .9 .3 .0 .2 .6 .0 .6 .8 .6 .7 .2 .3 .6 .8 r C IN 5 7 4 2 4 6 9 4 8 5 4 8 5 3 5 6 6 6 1 0 1 7 6 1 0 9 0 6 e 1 5 1 2 1 1 1 2 1 3 1 6 p 1 2 1 1 p . U n – io 4 6 5 P g P g .4 .0 .6 .4 .0 .8 .2 .3 .6 .9 .7 .0 .7 .8 .8 .0 .9 .2 .4 .6 .0 .2 .2 .4 .6 .0 ; U rea U ly in 6 7 8 4 7 5 9 3 1 7 8 7 5 4 4 5 4 6 0 0 1 0 7 5 0 5 3 1 n v te e 2 4 1 2 8 1 2 3 2 8 3 5 a 1 2 1 io ra llb g l S e e d t re tra o w 5 8 2 rs ne O h .8 .1 .2 .9 .2 .7 .4 .0 .2 .9 .5 .7 .3 .8 .7 .3 .0 .2 .8 .0 .7 .0 .7 .8 .7 .8 a C M ig 4 7 9 4 4 4 0 4 2 7 9 6 5 4 5 5 6 7 1 0 1 8 7 7 2 0 7 7 C h 5 4 3 2 0 1 5 1 2 8 5 3 l-K . 1 2 1 1 – ta n s N o a s ; C a 3 5 0 o n C l re O .4 .0 .0 .2 .3 .8 .6 .9 .0 .8 .3 .0 .4 .7 .1 .2 .1 .2 .0 .9 .2 .6 .3 .8 .2 .0 io – g a S 4 7 1 8 1 7 9 3 7 1 1 7 6 3 6 5 5 5 1 0 2 8 7 6 7 1 7 0 5 4 1 2 1 1 5 2 1 6 5 3 O icd 1 2 1 1 re e ; C ra n u g r m io e in 2 4 8 g M th E h e .8 .1 .3 .5 .4 .8 .2 .1 .3 .9 .2 .8 .0 .6 .8 .0 .9 .0 .8 .5 .1 .6 .6 .0 .9 .3 re – C ig 7 7 0 8 1 6 3 3 2 7 0 8 4 4 5 6 6 6 0 0 1 9 7 9 1 8 2 6 a U r. r o H llb ~ e 1 3 8 2 8 1 1 1 4 9 7 4 a o ; M e w 1 1 1 S n y ry, o ) io e ju . g – g n g n n O 0 o re , in in o 0 ; S a in ss e rs s tio ts n v s e e s c ,5 n io a ee llb l e e e g y e s ta r p s er 2 n e r Se illn n e n d d id lo re re w p to f w e a c m p illn ia ria n c tio a o n o m e o n e a ro a p c e L u e s o r m v to s t (u m t h v 0 d a e ry – rs a e s s u e h in ffic u a n lo O 0 v re e e fo a s e a e e le e d d n l S r 1 a s rk k s n c eig re e o rim m ; L e le d r p a a tra n e e tic tic o ic e ia w ju d id tra p k te rs p io / c c tio l c n s ic p is e s is v a ic tire e g e la N s ra ra t w irth in u o in v se n f d rd ro h re C re a o a to f d liza irth ly s o s n -re IO l p l p s e b s e – ia le S n tio t o ra rs in e ra is n u b b in s e t o ita n w n u to lc a n E th k f o lth N n e e rie v n p g d e a s le ic o a io rip e n rd n l d io ju t d a e s io in lo io rio u c io d b r; C rin n e E s s s o s s e s a f s n c e o e ta n a n iv ith n e ille d to s n s e ila to tio h IM e s tm g is g le e in lo ) le tm e e s k s e u e n a a C r o s re a e d s k a f h g s s s u b ia l b v ic e ra u R te – I D n s w e u O im p in l d in k im y (IF ic o im e im n ts n d im ic s ita a d A b l tre rte a x l tre n rn o n o ra id a s e p s m d rio B T I d g its ra its -s I d o d e f s I d m o I d e its g I d y rs s in u e a W A rs rs n ic d ; C B ru ita g is io p d tio o g v is lo ita b e e ru h u o e n u B rk o B B id u is B in ne ra f v C IC p o s p ra c tio e io e D W f d s f v a f v c W f re in s s u W f w ew W f p c f p f s f v f d W f p f n f h f b g v o F o h y e s e th u o f w c n d s a liza llb re s a rs O f C r o r o r o f C r o n e f C r o f n f C r o r o r o r o r o f C r o r o r o r o e e e E IN e f h e b e e o e s f h e e e e e e e e e e av to o b b d b r m o b u u g o irth b o b ffic b ita b b b o b b b b w rib th a U IC e o e o e e p e ra L S m m n m m rea q ra m m m s m m m m m m m ite cs ls ic te a fo rio te are o tra a A lu u a u u lu u h e a e lu tillb u lu u u o u u u lu u u u u s D e n d A a a re v a h a a o V B V N R N N V N S F S R A V S N S V N N H N N N V N N N N p – d R x ig in mo e s e ic ; D d v s G c a a ia in IN I – n y le b E lth lth s c e B ev n k d B a a e e ic W lo e ic te L C u c L q f s l h lth rs f h rv t S le E lth a a o e : * s re o e a e io s a F s W e n v n e s a l s e e : S F l h h l h tio ia tio th n a ta h ility c u T s 2 O e ra p a b o iav o a : u le A e u n b ila s re S s rio b E n c o k R e c e is av d b – te e n b E o S Ta A G O N R A a A S N b 76 Acta geographica Slovenica, 54-1, 2014 Special attention was directed to health as an important component of social wellbeing and its impact on the people's quality of life. This is also proved by various measures of economic development (Suhrcke et al. 2006; Buzeti et al. 2011, 17–28), in which an increasingly larger set of health indicators are used. Especially in light of the current economic crisis, in public health one can observe that the issue of mental disorders will become especially topical for the duration of the crisis (WHO 2011). More recent international and Slovenian studies are already reporting an increase in suicidal and violent behavior, increased drug and alcohol abuse, and increased incidence of depression and anxiety disorders, which are also connected with the general social insecurity, loss of jobs, and increased social and economic differ- ences between various population groups (Levy & Sidel 2009; Av~in et al. 2011; Mikuli}, Sándor and Leoncikas 2012). Therefore, in future planning and implementing social and healthcare policies, region- al differences and the related cultural differences will also have to be taken into account; these have a great impact on regional development (Urbanc, Boesch and Jelen 2007; Razpotnik, Urbanc and Nared 2009). Only in this way can the objectives of various strategies for ensuring wellbeing and health to all Slovenians be followed. 5 Conclusion This article presents a study of wellbeing in Slovenian regions using composite indicators. The study was based on the OECD methodological recommendations, but only objectively measureable indicators of wellbeing were included. Special attention was dedicated to health-related wellbeing, in which regional differences in general, occupational, and neonatal health, risk behaviors, and the availability of health and social care services were analyzed. The findings reveal a fairly heterogeneous pattern of wellbeing in Slovenian regions because there are significant differences in the development, living standards, and population health among certain regions. In this respect, Central Slovenia stands out as the region with the highest level of wellbeing. Western Slovenia is dominated by regions of moderately high wellbeing (the So~a, Coastal-Karst, and Upper Carniola regions), whereas eastern Slovenia is characterized by regions with the lowest levels of wellbeing (the Carinthia, Lower Sava, Mura, and Central Sava regions). These differences are likely to become even larger in the upcoming period of global crisis. The levels of health-related wellbeing differ considerably across Slovenian regions. Because the good health of the population is vital for reducing poverty, the long-term development of the society, and rais- ing the level of general wellbeing in the society, it is especially important for the government to work towards reducing differences between regions. Therefore, in the future more attention should be directed towards geographically specific data. Only a good knowledge of special regional features makes it possible to effec- tively plan and implement economic, social, environmental, and healthcare policy measures. 6 Acknowledgments This article was written as part of the research program Jezik, spomin in politike reprezentacije (Language, Memory, and Politics of Representation; P6-0347), co-funded by the Slovenian Research Agency (ARRS). 7 References Apohal Vu~kovi~, L., Kajzer, A., ^elebi~, T., Ferk, B., Kersnik, M., Kova~i~, S., Kmet Zupan~i~, R., Kraigher, T., Lavra~, I., Murn, A., Pe~ar, J., Primoì~, S., Zver, E. 2010: Socialni razgledi 2009. Ljubljana. Av~in, B. A., Ku~ina, A. U., Sarotar, B. N., Radovanovi}, M., Plesni~ar, B. K. 2011: The present global finan- cial and economic crisis poses an additional risk factor for mental health problems on the employees. Psychiatria Danubina 23-1. Boarini, R., Johansson, A., d'Ercole, M. M. 2006: Alternative measures of wellbeing. OECD social, employ- ment and migration working papers 33. Bole, D. 2004: Daily mobility of workers in Slovenia. Acta geographica Slovenica 44-1. DOI: http://dx.doi.org/ 10.3986/AGS44102 Bole, D. 2008a: Ekonomska preobrazba slovenskih mest. Geografija Slovenije 19. Ljubljana. 77 Lilijana [prah, Tatjana Novak, Jerneja Fridl, The wellbeing of Slovenia's population by region: comparison of indicators with … Bole, D. 2008b: Cultural industry as a result of new city tertiarization. Acta geographica Slovenica 48-2. DOI: http://dx.doi.org/10.3986/AGS48202 Bole, D. 2011: Changes in employee commuting: a comparative analysis of employee commuting to major Slovenian employment centers from 2000 to 2009. Acta geographica Slovenica 51-1. DOI: http:/ dx.doi.org/ 10.3986/AGS51104 Buzeti, T., Djomba, J. K., Gabrijel~i~ Blenku{, M., Ivanu{a, M., Jeri~ek Klan{~ek, H., Kel{in, N., Kofol Bric, T., Koprivnikar, H., Koro{ec, A., Kov{e, K., Mau~ec Zakotnik, J., Mihevc Ponikvar, B., Nadrag, P., Paulin, S., Pe~ar, J., Pe~ar ^ad, S., Rok Simon, M., Tom{i~, S., Truden Dobrin, P., Zadnik, V., Zver, E. 2011: Neenakosti v zdravju v Sloveniji. Ljubljana. Costanza, R., Hart, M., Posner, S., Talberth, J. 2009: Beyond GDP: the need for new measures of progress. The Pardee papers 4. Cowie, A. P., Lewis, J. W. 1989: Oxford advanced learner's dictionary. Oxford. Dernov{ek, M. Z., [prah, L. 2008: Assessment of mental health services in Slovenia with the European Service Mapping Schedule. Psychiatria Danubina 20-3. Diener, E. 2000: Subjective well-being: the science of happiness and a proposal for a national index. American Psychologist 55-1. DOI: http://dx.doi.org/10.1037/0003-066X.55.1.34 Diener, E., Seligman, M. E. P. 2009: Beyond money: toward an economy of well-being. Social Indicators Research Series 37. DOI: http://dx.doi.org/10.1007/978-90-481-2350-6_9 Gabrijel~i~ Blenku{, M., Koprivnikar, H., Drev, A., Vra~ko, P., Pirnat, N., Ho~evar, T., Vrdelja, M., Jeri~ek Klan{~ek, H., Pucelj, V., Kofol Bric, T., Martinovi~, B., Kranjc, I., Martinovi~, A. 2012: Vsevladni pristop za zdravje in blaginjo prebivalcev in zmanj{evanje neenakosti v zdravju. Ljubljana. Internet 1: http://pxweb.stat.si/pxweb/dialog/statfile2.asp (21. 10. 2011). Internet 2: http://www.oecdbetterlifeindex.org/countries/slovenia/ (21. 10. 2011). IVZ 2006–2008: Zdravstveni statisti~ni letopis Slovenije. In{titut za varovanje zdravja Republike Slovenije. Internet: http://www.ivz.si/Mp.aspx?ni=202 (29. 8. 2012). Kerber, B. 2012: Ageing at home with the help of information and communication technologies. Acta geo- graphica Slovenica 52-1. DOI: http://dx.doi.org/10.3986/AGS52107 Kneèvi} Ho~evar, D. 2012: Family farms in Slovenia: Who did the measures »setting up of young farmers« and »early retirement« actually address? Anthropological notebooks 18-1. Koreni~, R., Mavec, B. 2012: So ekonomske razlike med slovenskimi regijami velike? Statisti~ni urad repub- like Slovenije. Internet: http://www.stat.si/novica_prikazi.aspx?id=4878 (29. 8. 2012). Levy B. S., Sidel, V. W. 2009: The economic crisis and public health. Social medicine 4-2. Male{i~, K., Bregar, L., Rovan, J. 2009: Metodologija merjenja blaginje za ob~ine v Sloveniji. IB revija 3-4. Ljubljana. Matthews, E. 2006: Measuring wellbeing and societal progress: a brief history and the latest news. OECDJRC workshop »Measuring Wellbeing and Societal Progress.« Internet: http://crell.jrc.ec.europa.eu/Wellbeing/papers (30. 8. 2012). Mikuli} B., Sándor E., Leoncikas T. 2012: Experiencing the economic crisis in the EU: changes in living standards, deprivation and trust. European foundation for the improvement of living and working conditions. Internet: http://www.eurofound.europa.eu/pubdocs/2012/07/en/1/EF1207EN.pdf (29. 8. 2012). Nared, J. 2002: Razvitost slovenskih ob~in in nadaljnje razvojne perspektive. Geografski vestnik 74-2. Nared, J. 2007: Prostorski vplivi slovenske regionalne politike. Geografija Slovenije 16. Ljubljana. OECD 2008: Handbook on constructing composite indicators: methodology and user guide. Paris. OECD 2011: How's life? Measuring well-being. Paris. DOI: http:/ www.dx.doi.org/10.1787/9789264121164-en Pe~ar, J., Kava{, D. 2006: Metodologija izra~una indeksa razvojne ogroènosti za obdobje od 2007 do 2013. Delovni zvezek 6. Ljubljana. Perko, D. 1998: The regionalization of Slovenia. Acta geographica 38. Ravbar, M. 2011: Creative social groups in Slovenia: contribution to geographic studying of human resources. Acta geographica Slovenica 51-2. DOI: http://dx.doi.org/10.3986/AGS51204. Ravbar, M., Bole, D., Nared, J. 2005: A creative milieu and the role of geography in studying the compet- itiveness of cities: the case of Ljubljana Acta Geographica Slovenica 45-2. DOI: http://dx.doi.org/10.3986/ AGS45201 78 Acta geographica Slovenica, 54-1, 2014 Razpotnik, N., Urbanc, M., Nared, J. 2009: Prostorska in razvojna vpra{anja Alp. Georitem 12. Ljubljana. Rovan, J., Male{i~, K., Bregar, L. 2009: Blaginja ob~in v Sloveniji. Geodetski vestnik 53-1. Ljubljana. Strategija razvoja Slovenije/Slovenia's Development Strategy. Urad Republike Slovenije za makroekonomske analize in razvoj. Ljubljana, 2005. Stuckler, D., Basu, S., Suhrcke, M., Coutts, A., McKee, M. 2011: Effects of the 2008 recession on health: the first look at European data. The Lancet 378-9786. DOI: http://dx.doi.org/10.1016/S0140- 6736(11)61079-9 Stuckler, D., Basu, S., Suhrcke, M., McKee, M. 2009: The health implications of financial crisis: a review of the evidence. The Ulster medical journal 78-3. Suhrcke, M., McKee, M., Stuckler, D., Sauto Arce, R., Tsolova, S., Mortensen, J. 2006: The contribution of health to the economy in the European Union. Public health 120. DOI: http://dx.doi.org/10.1016/ j.puhe.2006.08.011. SURS 2006–2010: Slovenske regije v {tevilkah. Internet: http://www.stat.si/publikacije/pub_regije.asp (30. 8. 2012). Urbanc, M., Boesch, M., Jelen, I. 2007: Kultura in regionalna politika: kultura kot dejavnik regionalnega razvoja Alp. Geografski vestnik 79-1. WHO 2011: Impact of economic crises on mental health. Copenhagen. 79 Lilijana [prah, Tatjana Novak, Jerneja Fridl, Bla gi nja pre bi val cev Slo ve ni je po regi jah: pri mer ja va kazal ni kov s pou dar kom na zdrav ju Bla gi nja pre bi val cev Slo ve ni je po regi jah: pri mer ja va kazal ni kov s pou dar kom na zdrav ju DOI: http://dx.doi.org/10.3986/AGS54104 UDK: 913:330.59(497.4) 330.59:613(497.4) COBISS: 1.01 IZVLE^EK: Bla gi nja se v {ir {ih defi ni ci jah naj bolj pogo sto opi su je kot ve~ raz se èn pojem, opre de ljen s stanjem sre ~e, zdrav ja in pros pe ri te te. Ven dar se zara di raz li~ nih razu me vanj kon cep tual nih vpra {anj bla gi nje, stro kov nja ki sre ~u je jo s {te vil ni mi meto do lo{ ki mi teà va mi na podro~ ju nje ne ga mer je nja. Meto - do lo gi ja sestav lje nih kazal ni kov se vse bolj uve ljav lja tudi na podro~ ju mer je nja bla gi nje pre bi val cev. Zdrav je pred stav lja pomemb no podro~ je bla gi nje, z njim pa se pove zu je jo podob ni kazal ni ki kot pri mer je nju splo - {ne bla gi nje. V pris pev ku smo z me to do sestav lje nih kazal ni kov bla gi nje pri mer ja li raz li~ na podro~ ja bla gi nje in {e pose bej bla gi njo, pove za no z zdrav jem, med dva naj sti mi sta ti sti~ ni mi regi ja mi Slo ve ni je. Ugo tavljamo, da obsta ja jo med slo ven ski mi regi ja mi veli ke raz li ke v bla gi nji. V re gi jah zahod ne Slo ve ni je (Osred nje sloven - ska, Gori{ ka, Obal no-kra{ ka, Gorenj ska) je raven bla gi nje v glav nem vi{ ja, v re gi jah vzhod ne Slo ve ni je (Ko ro{ ka, Spod nje po sav ska, Pomur ska, Zasav ska) nì ja. Z iz je mo manj {ih odsto panj raven splo {ne bla gi nje v re gijah sov pa da z rav ni jo bla gi nje na podro~ ju zdrav ja. KLJU^NE BESEDE: geo gra fi ja, medi ci na, bla gi nja pre bi val cev, sestav lje ni kazal nik bla gi nje, zdrav je, regija, du{ev na mot nja Ured ni{ tvo je pre je lo pris pe vek 13. sep tem bra 2012. NASLOVI: dr. Lili ja na [prah Drù be no me di cin ski in{ti tut Znans tve no ra zi sko val ni cen ter Slo ven ske aka de mi je zna no sti in umet no sti Novi trg 2, SI – 1000 Ljub lja na, Slo ve ni ja E-po {ta: lili ja na.sprahazrc-sazu.si Tat ja na Novak Drù be no me di cin ski in{ti tut Znans tve no ra zi sko val ni cen ter Slo ven ske aka de mi je zna no sti in umet no sti Novi trg 2, SI – 1000 Ljub lja na, Slo ve ni ja E-po {ta: tno vakazrc-sazu.si mag. Jer ne ja Fridl Geo graf ski in{ti tut Anto na Meli ka Znans tve no ra zi sko val ni cen ter Slo ven ske aka de mi je zna no sti in umet no sti Gos po ska uli ca 13, SI – 1000 Ljub lja na, Slo ve ni ja E-po {ta: jer ne jaazrc-sazu.si 80 Acta geographica Slovenica, 54-1, 2014 1 Uvod Pre gled lite ra tu re o kon cep tual nih vpra {a njih bla gi nje in nje nem mer je nju raz gr ne {te vil ne meto do lo{ - ke teà ve (Matt hews 2006; Costan za in osta li 2009). Bla gi nja je kom plek sen pojem, opre de ljen kot sta nje sre ~e, zdrav ja in pros pe ri te te (Co wie in Lewis 1989, 1450). Zara di nje ne abstrakt no sti in ve~ di men zionalno - sti jo je mogo ~e meri ti le posred no z na bo rom izbra nih kazal ni kov, ki pa se mora jo tudi ustrez no ume{ ~a ti v do lo ~e no eko nom sko, social no in kul tur no oko lje ter vklju ~e va ti pred vsem tiste drù be ne vredno te, ki odra à jo poj mo va nje bla gi nje v kon kret nem oko lju. Zad nje ~ase smo pri ~a pove ~a ne mu zani ma nju strokovne in razi sko val ne jav no sti za preu ~e va nje bla gi nje ter {te vil nim raz pra vam o us trez nih meto dolo{kih pristo - pih nje ne ga mer je nja (Matt hews 2006). Pri tem se zastav lja osred nje vpra {a nje, ali sta bogas tvo in eko nom ski raz voj klju~ na za opre de lje va nje bla gi nje. Vse od usta no vi tve Orga ni za ci je za eko nom sko sode lo va nje in raz voj (OECD) leta 1961 je namre~ bru to doma ~i proi zvod (BDP) pred stav ljal osred nji kazal nik mer jenja in razu me va nja eko nom ske ga ter drù be ne ga napred ka, ki se ga je pove zo va lo tudi z blaginjo. Ven dar aktualne {tu di je kaè jo na ve~ plast nost poj ma bla gi nje, ki vklju ~u je tudi sub jek tiv ne in nema te rial ne sesta vi ne, kot so npr. sre ~a, zado voljs tvo, svo bo da, zdrav je, izo braz ba (Die ner in Selig man 2004; Costan za in osta li 2009). Na neka te re meto do lo{ ke in vse bin ske dile me, pove za ne z mer je njem bla gi nje, se je odzva la tudi OECD. Ob svo ji pet de set let ni ci je v ok vi ru pro jek ta »OECD kazal ni ki bla gi nje« (OECD 2011) pred sta vi la nov na~in sprem lja nja {ir {e poj mo va ne bla gi nje kot odgo vor na zah te ve po pri mer jal nih infor ma ci jah o ìv ljenj - skih raz me rah lju di v raz li~ no raz vi tih drà vah. OECD kazal ni ki bla gi nje vse bu je jo kazal ni ke mate rial nih raz mer ìv lje nja (do ho dek in bogas tvo, zapo sli tev in sta no vanj ske raz me re) in kako vo sti ìv lje nja (zdravs - tve no sta nje, uskla je nost dela in zaseb ne ga ìv lje nja, izo bra è va nje, drù be na pove za nost, civil na giba nja in vla da, kako vost oko lja, oseb na var nost in sub jek tiv na bla gi nja) (OECD 2011, 18 in 19). Ve~i na kazal - ni kov teme lji na sta ti sti~ nih podat kih, neka te ri pa so obli ko va ni tudi na pod la gi jav nom nenj skih anket. Ak tual na finan~ na in gos po dar ska kri za odpi ra {te vil ne nove vidi ke razu me va nja bla gi nje, tudi v po - ve za vi s se da nji mi sve tov ni mi in drù be ni mi izzi vi na podro~ jih pod neb nih spre memb, demo graf skih tren dov in jav ne ga zdrav ja (Stuc kler in osta li 2009). Doka zi govo ri jo, da gos po dar ska raz vi tost ni nuj no pove za - na z ve~ jo bla gi njo (Boa ri ni, Johans son in D'Er co le 2006; Miku li}, Sándor in Leon ci kas 2012). [e pose bej posta ja aktual no vpra {a nje, kako se bo kri za odra zi la na zdrav ju pre bi val cev. Izsled ki razi skav namre~ kaè - jo, da v ob dob ju kriz nara{ ~a jo spe ci fi~ ne bolez ni in umr lji vost zara di svo je vrst nih vzro kov (npr. stop nja samo mo ril no sti), poslab {u je se du{ev no zdrav je (ve~ depre siv nih in ank sioz nih motenj raz po lo è nja) in stop nja nasi lja v dru ì nah ter v {ir {em oko lju, pove ~u je pa se tudi zlo ra ba drog in alko ho la (Levy in Sidel 2009; Av~in in osta li 2011; Stuc kler in osta li 2011). Skrb vzbu ja tudi napo ved, da bo kri za poglo bi la nee na ko - sti v zdrav ju, kar se bo posle di~ no odra zi lo v nì ji rav ni bla gi nje {te vil nih pre bi vals tve nih sku pin (Bu ze ti in osta li 2011; Gabri jel ~i~ Blen ku{ in osta li 2012). Iz bolj {e va nje bla gi nje pre bi val cev je eden od pogla vit nih raz voj nih ciljev vsa ke drà ve, zato jo je tudi Slo ve ni ja vklju ~i la v Stra te gi jo raz vo ja Slo ve ni je (2005). ^etu di posa mez na drà va kot celo ta v med narodnem meri lu izka zu je dokaj viso ko raven bla gi nje, so zno traj nje lah ko pre cej{ nje raz li ke med posa mez ni mi obmo~ ji ozi ro ma regi ja mi. Regio nal ne raz li ke v bla gi nji so lah ko izvor social nih, eko nom skih in okoljskih teàv, ki zavi ra jo urav no te èn drù be ni in regio nal ni raz voj. Zato je pomemb no sprot no sprem lja nje geografsko pogo je ne rav ni bla gi nje, {e pose bej v lu ~i u~in ko vi te ga na~r to va nja in izva ja nja ukre pov pro stor skih, eko - nom skih in zdravs tve nih poli tik ter zago tav lja nja dostop no sti do jav nih sto ri tev, dela in kako vost nih bival nih raz mer (Ro van, Male {i~ in Bre gar 2009; Kerb ler 2012). 2 Namen razi ska ve in meto do lo{ ka poja sni la Na men pred stav lje ne razi ska ve je preu ~i ti splo {no bla gi njo posa mez nih sta ti sti~ nih regij Slo ve ni je in pre - ve ri ti raz li ke med nji mi z vi di ka raz li~ nih podro ~ij bla gi nje ter izbra nih kazal ni kov, pove za nih z zdrav jem. ^e prav se v zad njih letih na podro~ ju mer je nja bla gi nje vse bolj uve ljav lja jo meto do lo gi je s se stav lje - ni mi kazal ni ki (OECD 2008), pa tre nut no {e ne raz po la ga mo s »su per« kazal ni kom, ki bi obse gal vse nje ne dimen zi je, niti s po se bej defi ni ra nim, ki bi bil spre jet kot urad na mera bla gi nje. Zato smo na osno vi razpolòlji - vih sta ti sti~ nih podat kov in ob upo {te va nju meto do lo{ kih pri po ro ~il OECD (2008; 2011) za potre be te razi ska ve obli ko va li sestav lje ne kazal ni ke bla gi nje (SKB). V Slo ve ni ji poz na mo ve~ raz li~ nih regio na li zacij ozi ro ma deli tev Slo ve ni je (Per ko 1998), za na{o razi ska vo pa je zara di dostop no sti podat kov naj pri mernej{a deli tev na sta ti sti~ ne regi je. 81 Lilijana [prah, Tatjana Novak, Jerneja Fridl, Bla gi nja pre bi val cev Slo ve ni je po regi jah: pri mer ja va kazal ni kov s pou dar kom na zdrav ju 2.1 Kri te ri ji za izbor temelj nih kazal ni kov bla gi nje Pri vklju ~e va nju temelj nih socio de mo graf skih, eko nom skih, zdravs tve nih in okolj skih kazal ni kov v SKB smo upo {te va li vse bin sko pri mer nost kazal ni kov, nji ho vo raz po lò lji vost na rav ni sta ti sti~ nih regij in dostop - nost v re fe ren~ nem obdob ju (2006–2010) ter nji ho vo kako vost in zmò nost pov ze ma nja ve~ zna ~il no sti poja va (izra è nost v ob li ki indek sov, sto penj ali koe fi cien tov). Upo ra bi li smo sle de ~e sekun dar ne vire sta ti sti~ nih podat kov: 1. SI-STAT splet ni podat kov ni por tal Sta ti sti~ ne ga ura da RS (In ter net 1); 2. elek tron ske pub li ka ci je Slo ven ske regi je v {te vil kah, od 2006 do 2010 (SURS 2006–2010); 3. Zdravs tve ni sta ti sti~ ni leto pi si, od 2006 do 2008 (IVZ 2006–2008); 4. sta ti sti~ ne pri lo ge pub li ka ci je Ura da RS za makroe ko nom ske ana li ze in raz voj (Apo hal Vu~ ko vi~ in ostali 2010, 127). 3 Dolo ~a nje rav ni bla gi nje regij s po mo~ jo sestav lje nih kazal ni kov bla gi nje 3.1 Struk tu ra sestav lje ne ga kazal ni ka bla gi nje regi je Po dro~ ja ozi ro ma dimen zi je SKB smo opre de li li na pod la gi podro ~ij OECD kazal ni kov bla gi nje (OECD 2011). SKB vsa ke regi je vklju ~u je 70 te melj nih kazal ni kov, ki smo jih po vse bin ski sorod no sti raz vr sti li v 16 po - dro ~ij (di men zij) bla gi nje: doho dek, izo braz ba, sta no vanj ske raz me re, zapo sle nost, oko lje, splo {no zdrav je, var nost, star {ev sko vars tvo, social ni trans fer ji, raz po lò lji vost zdravs tve nih in social nih slùb, tve ga na vede - nja, poklic no zdrav je, peri na tal no zdrav je, sta bil nost part ner skih zvez, raz voj ne mò no sti in demo graf ski pro fil. [te vi lo vklju ~e nih temelj nih kazal ni kov se med dimen zi ja mi raz li ku je, kot je raz vid no iz vred nosti v ok le pa ju na sli ki 1. Sli ka 1: Struk tu ra sestav lje ne ga kazal ni ka bla gi nje regi je z vi di ka dimen zij bla gi nje in {te vi la vanje vklju ~e nih temelj nih kazal ni kov. Glej angle{ ki del pris pev ka. Sta ti sti~ ne podat ke temelj nih kazal ni kov, ki niso bili izra è ni v re la tiv nih oce nah (od stot ki, koe fi cien - ti, indek si), smo pred zasno vo sestav lje ne ga kazal ni ka pre ra ~u na li v pri mer lji ve eno te (gle de na {te vi lo pre bi val cev ozi ro ma povr {i no regi je) in jih stan dar di zi ra li. Iz nabo ra temelj nih kazal ni kov smo nato z mul - ti va riant no sta ti sti~ no meto do glav nih kom po nent, kate re namen je zmanj {a ti raz sè nost podat kov ozi ro ma v na {em pri me ru kazal ni kov ob ~im manj {i izgu bi infor ma cij, obli ko va li sestav lje ni kazal nik bla gi nje. V po - sa mez ni dimen zi ji bla gi nje smo zadr à li zgolj tiste temelj ne kazal ni ke, ki so bili vse bin sko smi sel no pove za ni s po dro~ jem in so gle de na rezul ta te meto de glav nih kom po nent poja sni li kar naj ve~ raz pr {e no sti podat - kov iz temelj nih kazal ni kov, ki sestav lja jo to kom po nen to. [te vil sko vred nost posa mez ne dimen zi je bla gi nje smo izra ~u na li z ob te ì tvi jo temelj nih kazal ni kov z dob lje ni mi kom po nent ni mi utè mi in dob lje no vred - nost pov pre ~i li za preu ~e va no obdob je. Za raz vr{ ~a nje regij gle de na raven bla gi nje po posa mez nih podro~ jih smo upo ra bi li linear no »STEN« trans for ma ci jo z raz po nom vred no sti od 1 do 10. Vred nost 1 je predstav - lja la naj manj {o izra ~u na no vred nost dimen zi je bla gi nje (naj nì ja raven bla gi nje na dolo ~e nem podro~ ju), vred nost 10 pa naj ve~ jo izra ~u na no vred nost dimen zi je bla gi nje (naj vi{ ja raven bla gi nje na dolo ~e nem podro~ ju). Vred nost SKB je bila izra ~u na na kot pov pre~ na vred nost vseh 16 di men zij bla gi nje v po sa mezni sta ti sti~ ni regi ji. Regi je smo nato gle de na nji ho ve vred no sti SKB raz vr sti li v {ti ri kate go ri je: regi je visoke bla gi nje, regi je zmer no viso ke bla gi nje, regi je zmer no niz ke bla gi nje in regi je niz ke bla gi nje. Pre gled ni ca 1 kaè temelj ne kazal ni ke, vklju ~e ne v di men zi je bla gi nje, in nji hov vpliv na bla gi njo. Z zna - kom (+) so ozna ~e ni kazal ni ki, kjer nji ho ve vi{ je vred no sti (npr. obseg delav no aktiv ne ga pre bi vals tva) pris pe va jo k vi{ ji rav ni bla gi nje v re gi ji. Znak (–) je pred kazal ni ki, kjer nji ho ve vi{ je vred no sti (npr. stopnja brez po sel no sti) zni ù je jo raven bla gi nje v re gi ji. Pri tistih kazal ni kih, za kate re sta ti sti~ ni podat ki na regio - nal ni rav ni niso bili dostop ni za refe ren~ no obdob je (2006–2010), smo upo {te va li kraj {e refe ren~no obdob je (tri ozi ro ma {ti ri leta). 82 Acta geographica Slovenica, 54-1, 2014 Pre gled ni ca 1: Pre gled vklju ~e nih temelj nih kazal ni kov v se stav ljen kazal nik bla gi nje regi je in nji hov vpliv na bla gi njo. PODRO^JE TEMELJNI KAZALNIK VPLIV NA PODATKOVNI VIR BLAGINJE BLAGINJO IN REFEREN^NO OBDOBJE Do ho dek In deks BDP (bru to doma ~e ga proi zvo da) na pre bi val ca a + SURS, 2006–2008 BDP na pre bi val ca, izra èn v stan dar dih kup ne mo~i + SURS, 2006–2008 Pov pre~ na mese~ na neto pla ~a na zapo sle no ose bo + SURS, 2006–2010 Izo braz ba De lè pre bi val cev, sta rih 22–64 let, brez izo braz be, z ne do kon ~a no ali dokon ~a no osnov no {ol sko izo braz bo – SURS, 2006–2009 De lè pre bi val cev, sta rih 22–64 let, s sred nje {ol sko izo braz bo + SURS, 2006–2009 De lè pre bi val cev, sta rih 22–64 let, z vi{ je ali viso ko {ol sko izo braz bo + SURS, 2006–2009 [te vi lo {tu den tov gle de na delov no aktiv no pre bi vals tvo + SURS, 2006–2009 De leòdra slih oseb, sta rih 25–64 let, vklju ~e nih v vse ìv ljenj sko izo bra è va nje + SURS, 2006–2009 Sta no vanj ske Pov pre~ na povr {i na sta no va nja na ose bo + SURS, 2006–2010 raz me re [te vi lo dokon ~a nih sta no vanj (no vo grad nje, pove ~a ve, spre mem be namemb no sti) + SURS, 2006–2010 Za po sle nost De lè delov no aktiv ne ga pre bi vals tva + SURS, 2006–2010 Stop nja delov ne aktiv no sti + SURS, 2006–2009 Stop nja regi stri ra ne brez po sel no sti – SURS, 2006–2010 De lè brez po sel nih z os nov no {ol sko izo braz bo – SURS, 2006–2010 De lè brez po sel nih z vi{ je- oz. viso ko {ol sko izo braz bo – SURS, 2006–2010 [te vi lo pro stih delov nih mest gle de na delov no aktiv no pre bi vals tvo + SURS, 2006–2010 De lè delov no aktiv ne ga pre bi vals tva, sta re ga 55–64 let + SURS, 2007–2009 [te vi lo aktiv nih pod je tij gle de na delov no aktiv no pre bi vals tvo + SURS, 2006–2009 Oko lje Ko li ~i na vode, dobav lje ne gos po dinjs tvom iz jav ne ga vodo vo da + SURS, 2006–2010 De lè nepre ~i{ ~e ne odpad ne vode, izpu{ ~e ne iz kana li za ci je – SURS, 2007–2009 Oce nje na {ko da zara di ele men tar nih nesre~, izra è na v de le ù regio nal ne ga BDP – SURS, 2006–2008 Splo {no zdrav je [te vi lo zdrav ni{ kih recep tov – IVZ, 2007–2009 Stop nja hos pi ta li za ci je zara di bolez ni – IVZ, 2006–2009 [te vi lo pri me rov bolez ni obto ~il kot naj po go stej {ih vzro kov smr ti – IVZ, 2006–2009 [te vi lo pri me rov bolez ni pre ba vil kot naj po go stej {ih vzro kov smr ti – IVZ, 2006–2009 [te vi lo obi skov v pri mar nem zdravs tvu zara di endo kri nih, pre hran skih in pre snov nih motenj – IVZ, 2006–2008 [te vi lo obi skov v pri mar nem zdravs tvu zara di du{ev nih in vedenj skih motenj – IVZ, 2006–2009 [te vi lo obi skov v pri mar nem zdravs tvu zara di bolez ni obto ~il – IVZ, 2006–2008 [te vi lo obi skov v pri mar nem zdravs tvu zara di bolez ni pre ba vil – IVZ, 2006–2008 [te vi lo obi skov v pri mar nem zdravs tvu zara di bolez ni mi{i~ no-ske let ne ga siste ma in vezi va – IVZ, 2006–2008 Var nost [te vi lo obso je nih pol no let nih oseb ne gle de na vrsto kaz ni ve ga deja nja – SURS, 2006–2010 [te vi lo obso je nih pol no let nih oseb gle de na kaz ni va deja nja zoper zakon sko zve zo, dru ì no in otro ke – SURS, 2006–2010 [te vi lo obso je nih mla do let nih oseb ne gle de na vrsto kaz ni ve ga deja nja – SURS, 2006–2010 [te vi lo pri me rov samo po{ kod be ne ga vede nja – SURS, 2006–2009 [te vi lo pri me rov napa da na dru go ose bo – SURS, 2006–2009 Star {ev sko De leòtrok v vrt cih med vse mi otro ki, sta ri mi 1–5 let + SURS, 2006–2009 vars tvo [te vi lo upra vi ~en cev do dela s skraj {a nim delov nim ~asom zara di star {evs tva + SURS, 2006–2009 [te vi lo upra vi ~en cev do o~e tov ske ga nado me sti la zara di star {evs tva + SURS, 2006–2009 [te vi lo skle nje nih zakon skih zvez + SURS, 2006–2010 So cial ni trans fer ji [te vi lo pre jem ni kov denar nih social nih pomo ~i – SURS, 2006–2009 De lè {ti pen di stov med dija ki in {tu den ti + SURS, 2008–2010 Raz po lò lji vost [te vi lo zdrav ni kov + SURS, 2007–2009 zdravs tve nih [te vi lo medi cin skih sester + SURS, 2007–2009 in social nih slùb [te vi lo bol ni {ni~ nih postelj + SURS, 2007–2009 [te vi lo leì{~ v do mo vih za osta re le + SURS, 2006–2009 83 Lilijana [prah, Tatjana Novak, Jerneja Fridl, Bla gi nja pre bi val cev Slo ve ni je po regi jah: pri mer ja va kazal ni kov s pou dar kom na zdrav ju Tve ga na vede nja [te vi lo hudo po{ ko do va nih v cest no pro met nih nesre ~ah – SURS, 2006–2009 [te vi lo umr lih v cest no pro met nih nesre ~ah – SURS, 2007–2009 Stop nja hos pi ta li za ci je zara di samo mo ra – IVZ, 2006–2009 [te vi lo samo mo rov – IVZ, 2006–2009 [te vi lo obrav nav zara di uì va nja alko ho la – IVZ, 2006–2009 [te vi lo obrav nav zara di zlo ra be drog – IVZ, 2006–2009 Po klic no zdrav je [te vi lo pri jav lje nih po{ kodb pri delu gle de na delov no aktiv no pre bi vals tvo – IVZ, 2006–2009 De leìzgub lje nih kole dar skih dni na zapo sle ne ga zara di bol ni{ ke ga sta le à – IVZ, 2006–2010 In deks frek ven ce (IF) b – IVZ, 2006–2010 Re snost (R) bol ni{ ke ga sta le à c – IVZ, 2006–2010 Stop nja bol ni {ni~ nih obrav nav zara di bolez ni – IVZ, 2006–2009 Pov pre~ no tra ja nje hos pi ta li za ci je zara di bolez ni – IVZ, 2006–2009 Pe ri na tal no Mr tvo ro je nost – IVZ, 2007–2009 zdrav je De lè porod nic s car skim rezom v anam ne zi – IVZ, 2006–2009 De lè novo ro jen~ kov z niz ko porod no teò (pod 2500 g) med ìvo ro je ni mi – IVZ, 2007–2009 Sta bil nost [te vi lo raz vez gle de na {te vi lo pre bi val cev v po sa mez ni regi ji – SURS, 2006–2010 part ner skih zvez Raz voj ne In deks raz voj ne ogro è no sti f – UMAR, 2007–2010 mò no sti De mo graf ski Go sto ta nase lje no sti – SURS, 2006–2009 pro fil De lè ìvo ro je nih + SURS, 2006–2010 De leùmr lih – SURS, 2006–2010 Skup ni pri rast pre bi vals tva (na rav ni in seli tve ni pri rast) + SURS, 2006–2010 Koe fi cient sta rost ne odvi sno sti d – SURS, 2006–2010 In deks sta ra nja e – SURS, 2006–2010 De lè kme~ ke ga pre bi vals tva – SURS, 2006–2010 Opom be: a In deks BDP na pre bi val ca pri mer ja bru to drù be ni proi zvod na pre bi val ca regi je v pri mer ja vi s po dat kom za Slo ve ni jo v is tem letu. b Indeks frek ven ce odra à {te vi lo pri me rov odsot no sti z dela zara di bol ni{ ke odsot no sti na 100 za po sle nih v enem letu. c Resnost bol ni{ ke ga sta le à je pov pre~ no tra ja nje ene odsot no sti z dela zara di bolez ni, po{ kod be ali dru ge ga zdravs tve ne ga vzro ka. d Koe fi cient sta rost ne odvi sno sti je raz mer je med mla dim (sta ri od 0 do 14 let) in sta rim (nad 65 let) ter delov no spo sob nim (nad 15 let) pre bi vals tvom. e Indeks sta ra nja je raz mer je med sta rim (sta ri 65 let ali ve~) in mla dim pre bi vals tvom (sta ri od 0 do 14 let), pom no è no s 100. f Indeks raz voj ne ogro è no sti je izra ~u nan iz 11 ka zal ni kov (ka zal ni ki raz vi to sti, raz voj ne ogro è no sti in raz voj nih mò no sti) (Pe ~ar in Kava{ 2006). Opre de li tve izra zov a, d–f so pov ze te iz podat kov nih zbirk (In ter net 1), defi ni ci ji b–c pa iz Zdravs tve ne ga sta ti sti~ ne ga leto pi sa (IVZ 2006). 3.2 Pri mer ja va regij gle de na raz li~ ne rav ni in podro~ ja bla gi nje Sli ka 2 pri ka zu je pri mer ja vo social nih, demo graf skih, zdravs tve nih, eko nom skih in okolj skih dimen zij blagi - nje med slo ven ski mi sta ti sti~ ni mi regi ja mi. Regi je smo gle de na vred nost SKB raz vr sti li v {ti ri sku pi ne (raz pon vred no sti SKB: od 7,6 do 3,3; inter val 1,07) in so na sli ki obar va ne v raz li~ nih odten kih oran`ne bar ve: • 1. sku pi na: Regi je viso ke bla gi nje (SKB = 7,6 do 6,52): Osred nje slo ven ska regi ja (SKB = 7,58). • 2. sku pi na: Regi je zmer no viso ke bla gi nje (SKB = 6,53 do 5,45): Gori{ ka regi ja (SKB = 5,94), Obal no-kra{ka regi ja (SKB = 5,90), Gorenj ska regi ja (SKB = 5,78) in Notranj sko-kra{ ka regi ja (SKB = 5,20). • 3. sku pi na: Regi je zmer no niz ke bla gi nje (SKB = 5,46 do 4,38): Savinj ska regi ja (SKB = 4,91), Jugovz - hodna Slo ve ni ja (SKB = 4,88) in Podrav ska regi ja (SKB = 4,75). • 4. sku pi na: Regi je niz ke bla gi nje (SKB = 4,39 do 3,32): Koro{ ka regi ja (SKB = 4,21), Spod nje po sav ska regija (SKB = 4,04), Pomur ska regi ja (SKB = 3,45) in Zasav ska regi ja (SKB = 3,37). Med regi ja mi so se poka za le pre cej{ nje raz li ke v bla gi nji, pri ~emer izra zi to izsto pa Osred nje slo ven - ska regi ja, kot regi ja z naj vi{ jo, ter Pomur ska in Zasav ska kot regi ji z naj nì jo rav ni jo splo {ne bla gi nje (sli ka 2). V za hod nem delu Slo ve ni je se je obli ko va la sku pi na regij z vi{ ji mi ravn mi splo {ne bla gi nje (Osred nje slo - ven ska, Gori{ ka, Obal no-kra{ ka in Gorenj ska regi ja) in v vzhod nem delu sku pi na regij z naj nì ji mi ravn mi splo {ne bla gi nje (Po drav ska, Koro{ ka, Spod nje po sav ska, Zasav ska in Pomur ska regi ja). V re gi jah z vi{ jo rav ni jo splo {ne bla gi nje se pojav lja tudi vi{ ja raven bla gi nje na sko raj vseh dru gih podro~ jih. Pre bi val ci v teh regi jah ima jo vi{ jo izo braz bo, ve~ dohod ka, pre bi va jo v bolj {ih sta no vanj skih in okolj skih raz me - rah, ima jo tudi ve~ zapo sli tve nih mò no sti in bolj {e raz me re gle de star {ev ske ga vars tva. Hkra ti so to regije z ve~ ji mi mò nost mi za raz voj in iz ugod nej {im demo graf skim pro fi lom. 84 Acta geographica Slovenica, 54-1, 2014 Sli ka 2: Pri mer ja va slo ven skih regij gle de na raz li~ ne rav ni in podro~ ja bla gi nje. Glej angle{ ki del pris pev ka. 3.3 Pri mer ja va regij gle de na temelj ne kazal ni ke bla gi nje, pove za ne z zdrav jem Pri mer ja va regij gle de na raven bla gi nje podro ~ij, pove za nih z zdrav jem, je poka za la, da se v re gi jah visoke in zmer no viso ke bla gi nje odra à tudi na splo {no vi{ ja raven bla gi nje na podro~ ju splo {ne ga, poklic ne - ga in peri na tal ne ga zdrav ja ter raz po lò lji vo sti zdravs tve nih in social nih slùb (pri mer ja va stolp cev na sli ki 2; vi{ je vred no sti dimen zij v sklo pu SKB v pre gled ni ci 2). Pre ve ri li smo tudi, kako se po regi jah raz vr{ ~a jo neka te ri izbra ni temelj ni kazal ni ki bla gi nje, pove za ni z zdrav jem. Ker se bla gi nja na podro~ ju zdrav ja lah - ko pove zu je tudi z uì va njem drog in alko ho la, samo mo ril nim vede njem in po{ kod ba mi v cest no pro met ni nesre ~ah, smo vklju ~i li tudi kazal ni ke, ki sestav lja jo dimen zi jo bla gi nje tve ga na vede nja (pre gled ni ca 2). V pre gled ni ci 2 lah ko vidi mo, da splo {na raven bla gi nje ne odra à ved no bla gi nje na posa mez nih podro~ - jih v do lo ~e ni regi ji. Tako se Osred nje slo ven ska regi ja (re gi ja viso ke bla gi nje gle de na vred nost SKB) pri ve~i ni temelj nih kazal ni kov uvr{ ~a na mesta, ki jih lah ko pove zu je mo z ve~ jo bla gi njo, ven dar pa se v pri - mer ja vi z os ta li mi regi ja mi na podro~ ju zdrav ja pojav lja jo tudi neka te ra odsto pa nja, npr. naj vi{ ja stop nja hos pi ta li za ci je zara di bolez ni, dokaj visok delè novo ro jen~ kov z niz ko porod no teò, ve~ je {te vi lo obrav - nav zara di zlo ra be drog in ve~ huje po{ ko do va nih v cest no pro met nih nesre ~ah. Tak {na odsto pa nja lah ko opa zi mo tudi v dru gih regi jah. V Za sav ski regi ji (z naj nì jo rav ni jo splo {ne bla gi nje) pre vla du je niz ka raven bla gi nje na podro~ ju zdrav ja, ven dar pa izsto pa v pri mer ja vi z os ta li mi regi ja mi z re la tiv no dobrim stanjem na neka te rih podro~ jih, kot so npr. naj manj obi skov v pri mar nem zdravs tvu zara di bolez ni mi{i~ no-ske - let ne ga siste ma in vezi va in manj hudo po{ ko do va ni mi v cest no pro met nih nesre ~ah, manj mrtvo ro je ni mi otro ci in z re la tiv no dobro raz po lò lji vost jo leì{~ v do mo vih za osta re le. 4 Raz pra va Za mer je nje bla gi nje so {e do nedav ne ga pre vla do va li pri sto pi, ki so kot prib li èk oce ne bla gi nje upo rablja li bodi si makroe ko nom ske sta ti sti ke, kot je npr. BDP, bodi si sub jek tiv ne pre so je lju di o nji ho vem zado voljs - tvu s ka ko vost jo ìv lje nja. Izka za lo se je, da sub jek tiv ne pre so je bla gi nje v ok vi ru med na rod nih in medre gij skih pri mer jav niso zanes lji ve, saj jih mo~ no pogo ju je na eni stra ni kul tur ni kon tekst in na dru gi raz li~ ni psi - ho lo{ ki dejav ni ki (Die ner 2000). Zato se na podro~ ju mer je nja bla gi nje vse bolj uve ljav lja meto da sestav lje nih kazal ni kov (Matt hews 2006; OECD 2011), ki smo jo upo ra bi li tudi v pred stav lje ni razi ska vi. Kljub temu, da je v ok vi ru med na rod nih pri mer jav Slo ve ni ja obrav na va na kot homo ge na regio nal - na eno ta, pa {te vil ne doma ~e eko nom ske, geo graf ske, socio lo{ ke, antro po lo{ ke in zdravs tve ne {tu di je kaè jo, da se na rav ni nje nih teri to rial nih enot (ob ~in, sta ti sti~ nih regij) pojav lja jo veli ke raz li ke in poseb no sti, ki se posle di~ no izka zu je jo tudi v do sto pu do sto ri tev in bla ga ter infra struk tu re, v eko nom skih in zapo - sli tve nih mò no stih, v do stop no sti in raz po lò lji vo sti zdravs tve nih ter social nih sto ri tev in drug je (Na red 2002; Bole 2004; Rav bar, Bole in Nared 2005; Nared 2007; Bole 2008a, Bole 2008b; Der nov {ek in [prah 2008; Bole 2011; Rav bar 2011; Kne è vi} Ho~e var 2012; Kore ni~ in Mavec 2012). V raz li~ nih med - na rod nih {tu di jah osta ja jo te raz li ke in poseb no sti Slo ve ni je neo pa è ne, saj so podat ki agre gi ra ni na dràv ni rav ni. To lah ko raz be re mo tudi iz izsled kov {tu di je OECD (2011), v ka te ri so s po mo~ jo inte rak tiv ne ga orod ja mer je nja bla gi nje opra vi li med na rod no pri mer ja vo bla gi nje v dr à vah ~la ni cah OECD. Slo ve ni ja je med 34 ~la ni ca mi OECD zased la skup no 21. me sto. Pri neka te rih dimen zi jah bla gi nje se je uvr sti la blizu pov pre~ ja dràv OECD (zdrav je, vklju ~e nost v drù bo), ali celo vi{ je (za po sle nost, oseb na var nost), pod pov pre~ je dràv OECD pa je zdr sni la pri dimen zi jah sta no va nje in zado voljs tvo z ìv lje njem (In ter net 2). V pris pev ku nas je zani ma la raven bla gi nje v sta ti sti~ nih regi jah Slo ve ni je, kot jo omo go ~a pri la go - jena meto do lo gi ja OECD kazal ni kov. Rezul ta ti so poka za li, da se regi je gle de na splo {no raven bla gi nje, opre de lje no s sred njo vred nost jo SKB, med seboj zelo raz li ku je jo, saj je bil raz pon vred no sti SKB med regi ja mi pre cej {en, od 7,58 do 3,37. Pose bej je zani mi vo sta nje bla gi nje na podro~ ju zdrav ja, ki v ne ka te - rih regi jah odsto pa od sta nja splo {ne bla gi nje. Uje ma nje ocen splo {ne bla gi nje in bla gi nje na podro~ ju zdrav ja potr ju je spoz na nje, da viso ka raven bla gi nje sov pa da z gos po dar sko in social no bolje raz vi ti mi urba ni mi sre di{ ~i, ven dar pa neu je ma nje teh ocen v ne ka te rih regi jah tudi opo zar ja na to, da se ugod ne 85 Lilijana [prah, Tatjana Novak, Jerneja Fridl, Bla gi nja pre bi val cev Slo ve ni je po regi jah: pri mer ja va kazal ni kov s pou dar kom na zdrav ju 0 0 7 A ,9 ,7 ,6 ,3 ,7 ,3 ,0 ,3 ,6 ,7 ,1 ,7 ,8 ,2 ,1 ,4 ,0 ,5 ,7 ,2 ,1 ,7 ,9 ,5 ,4 ,0 Z 0 8 9 7 1 0 0 5 2 1 9 8 6 3 5 6 0 2 1 0 2 6 9 3 4 0 7 4 a 4 5 8 3 6 3 4 3 1 6 2 6 n 1 1 1 do z h 0 1 3 vo O ,1 ,1 ,7 ,4 ,8 ,6 ,8 ,7 ,7 ,5 ,9 ,2 ,6 ,3 ,3 ,4 ,4 ,2 ,7 ,1 ,6 ,9 ,5 ,8 ,1 ,0 gu P e 1 9 5 6 3 3 2 4 4 2 5 7 3 6 5 6 3 5 1 0 2 1 8 5 6 4 7 7 J iz k je 6 5 3 2 7 2 6 3 2 1 8 3 3 1 2 1 – n i n V g J i je g la 4 9 1 i ja P b ,2 ,6 ,0 ,3 ,6 ,1 ,6 ,0 ,0 ,6 ,5 ,9 ,2 ,7 ,4 ,7 ,9 ,1 ,9 ,9 ,5 ,3 ,6 ,4 ,1 ,3 g S re 4 8 5 7 8 5 6 4 8 7 5 7 3 6 5 6 3 4 0 0 2 3 6 3 3 4 8 4 4 3 9 2 8 1 4 3 1 5 1 5 re 1 1 1 akj s 9 1 2 inva O ,7 ,9 ,7 ,3 ,8 ,6 ,1 ,6 ,7 ,9 ,3 ,2 ,6 ,9 ,4 ,9 ,0 ,4 ,7 ,4 ,7 ,9 ,4 ,5 ,1 ,0 K 3 7 1 5 7 2 5 4 6 2 1 6 3 5 4 6 3 4 1 0 2 7 4 5 9 3 8 4 S 5 4 4 3 7 2 5 2 1 8 4 5 1 2 1 –A ; S 3 6 1 i ja D ,7 ,6 ,7 ,9 ,9 ,3 ,0 ,3 ,7 ,3 ,8 ,2 ,6 ,5 ,0 ,3 ,2 ,2 ,7 ,2 ,3 ,9 ,8 ,4 ,3 ,3 g P 4 8 0 5 5 4 9 4 2 9 0 8 2 6 5 7 5 5 1 0 2 3 4 6 2 1 5 0 3 4 1 2 8 1 3 2 2 8 5 4 re 1 2 1 a k o je { r n ra e i n g 4 3 2 -ko V la ,3 ,7 ,4 ,6 ,8 ,5 ,9 ,5 ,3 ,6 ,3 ,0 ,5 ,9 ,4 ,8 ,4 ,2 ,3 ,0 ,3 ,6 ,8 ,5 ,1 ,3 k J zm 5 7 8 1 6 4 1 4 4 9 8 8 2 8 4 6 5 5 1 0 2 4 6 4 8 7 6 0 b 2 4 9 3 8 1 2 2 1 6 2 5 j sn i je e 1 1 1 g iz k tra re n o 4 5 5 N A ,2 ,1 ,6 ,6 ,2 ,7 ,9 ,5 ,6 ,2 ,4 ,5 ,2 ,7 ,3 ,0 ,3 ,3 ,7 ,4 ,8 ,6 ,6 ,8 ,0 ,5 – S 5 8 6 9 3 2 6 4 6 2 6 7 4 5 4 5 4 6 1 0 2 6 6 5 8 2 5 6 O 4 3 2 3 7 2 4 2 1 7 4 4 1 2 1 , N i jag 3 0 9 re O ,7 ,9 ,2 ,5 ,6 ,9 ,6 ,2 ,2 ,8 ,9 ,6 ,9 ,3 ,0 ,2 ,6 ,0 ,6 ,8 ,6 ,7 ,2 ,3 ,6 ,8 a N 5 7 4 2 4 6 9 4 8 5 4 8 5 3 5 6 6 6 1 0 1 7 6 1 0 9 0 6 k 1 5 1 2 1 1 1 2 1 3 1 6 j s 1 2 1 1 nreo 4 6 5 G O o je ,4 ,0 ,6 ,4 ,0 ,8 ,2 ,3 ,6 ,9 ,7 ,0 ,7 ,8 ,8 ,0 ,9 ,2 ,4 ,6 ,0 ,2 ,2 ,4 ,6 ,0 – . G r n i n 6 7 8 4 7 5 9 3 1 7 8 7 5 4 4 5 4 6 0 0 1 0 7 5 0 5 3 1 O . e g 2 4 1 2 8 1 2 3 2 8 3 5 i ja a k la 1 2 1 ; G g . zm b i ja re tu zro e g a v i je k 5 8 2 k re s le a B g o ,8 ,1 ,2 ,9 ,2 ,7 ,4 ,0 ,2 ,9 ,5 ,7 ,3 ,8 ,7 ,3 ,0 ,2 ,8 ,0 ,7 ,0 ,7 ,8 ,7 ,8 a v m ge O a e re is 4 7 9 4 4 4 0 4 2 7 9 6 5 4 5 5 6 7 1 0 1 8 7 7 2 0 7 7 k n v 5 4 3 2 0 1 5 1 2 8 5 3 { s n e 1 2 1 1 ra a e Z tv -k v s o – ih v 3 5 0 l n A n ra R ,4 , 0 ,0 ,2 ,3 ,8 ,6 ,9 ,0 ,8 ,3 ,0 ,4 ,7 ,1 ,2 ,1 ,2 ,0 ,9 ,2 ,6 ,3 ,8 ,2 ,0 a le b ; Z s zd G 4 7 1 8 1 7 9 3 7 1 1 7 6 3 6 5 5 5 1 0 2 8 7 6 7 1 7 0 a 5 4 1 2 1 1 5 2 1 6 5 3 O i ja o g 1 2 1 1 g p e . – g B re za m ke a 0 ru k 0 je je 2 4 8 ; O v r s 1 li d S i n ,8 , 1 , 3 ,5 , 4 , 8 , 2 , 1 , 3 , 9 ,2 , 8 , 0 , 6 ,8 , 0 , 9 , 0 , 8 , 5 , 1 ,6 ,6 , 0 ,9 ,3 i ja u a ra a O g 7 7 0 8 1 6 3 3 2 7 0 8 4 4 5 6 6 6 0 0 1 9 7 9 1 8 2 6 g m e i ja viso la 1 3 8 2 8 1 1 1 4 9 7 4 re o ti n b b 1 1 1 a s P d o o z zd k k a re g – t n { n ri{ o o O s o za i ; P d e G o i, p v a – i ja e z n o lez n g i R g k o e z n esre ~ah i{ leo , p i re d n i le n ; G a l n je i b le k o i b ra ih s z n o zi h i ja s d i n a o le e a g v i b ra g l c n ò za a a p o i b et n ~ la d d ra re s la a u m te m re o a o ra za i zara d i b ra a s o h k p b i v za o la b tv zi v ro s s e a d n n p e m o g n je za e ja z n v lu za a d o o lk le e n la ~ e ra n / re le v i ro v d e ra j i n v ro ih m a re o ro * p o n ravs tvu in n i je d lo b za c m o i m a ja ta s p ti z d d B a te a ri d d v n t n n e s s S o o K n i b zd o p à a p e i s b je ti z d v d zd m ih n zo o je d a o n – s t n p S m b k le v li za v cest n m ra lj d o o a e m te P B to ra em B d à ta B re ro B ra ì v B r re t n s n V p is o r s ra i ta iz k o ih ro te te za o d E K ih e za r n k K k a le s b p K im K p za i u i zlo K s s s ; S s c a ar n s { d ta a s k o ih d d e o v O o i ja d e z li~ IJ S j s a S g o o S z n S va n S Z IK o a ìv v i je le s ) i je p o g n re c ri m n g e r s v t n s – o e v p o a k ih h v o a d v d s c ra ra v S v e ra N N e ri m o e v ih ih m re E L ih p d t n ih k g n e e (IF i{ je c k za za v k n o a ro je A zi je k li za v e zi je n ih k e i~ n zi je ~ zi je c li za ro v v zi je o s ; O k e n i za { ko i~ IM Z n le n l n n n s n ) m n o n d { e i{ v v v v p e e n i{ c o ja e t g e o v a a e i k in n je ja i k n i ta o lje n i { ic je i ta m n n n v ro ri m D A v p k in k v i n lje l n e s n 0 p p o v v v i c i { ~ g o p tra l n T o ro I K im s v ) b l n s ra im tra im d im o r lih im o i s ih i sko -s b o k o d o n o 0 d o m ra ra ra e l n la K o za S N t d b n b o t d ri ja u t d ro v 5 t d u m a b b t d o ì{ b i lo n – v ~ a O J s h v n s i b t (R b n~ s je o o 2 s h s L o zd ja o e o i~ o p d fre s ja o ro d o h u ja s o o o zd m b le ik O te re i k N s p D E n n { i{ n ìzg ra o n re n ò p ` n o n n n l n ; K { v d i lo p i lo u d i lo k n p p d d i lo p i lo i lo i lo d i lo i lo i lo i lo za à o lj n E M v v d m v le za e s v le le (p v v v v v v v v a i ja e R E re te to te te vi lo re te e d e to o re r tv e e re te vi lo te to te te te re te te te te g ra p i k d m V T V [ S [ [ V [ D In R S P V M D D V [ [ S [ [ [ V [ [ [ [ je n re o a e à i te E lje k v s c le n J n ta v e ta ra IN s v e ra k s G je d a o A v s g ja `b P fre e : Izb L je je ra t – v v n s lu s k B - k 2 e o e i{ a B ra s K – E ra zd d o e ih S D d l n i c J zd n ih In o n ^ zd o l n v ` lji v e l n : * ; P a t b d a e : O on n ta n lo tv ia v i ja e s le R { a a o s c a n b o g v n D lic j { lo k o e ri n g z p v m s re O p o e e o e v a ra s rak lo p R P P S P P T R zd in O S O b 86 Acta geographica Slovenica, 54-1, 2014 ìv ljenj ske in okolj ske raz me re ob~in ne odsli ka va jo ved no tudi v nji ho vi gos po dar ski in drù be ni raz vi - to sti (Ma le {i~, Bre gar in Rovan 2009, 47 in 51). Po seb no pozor nost smo name ni li zdrav ju kot pomemb ni kom po nen ti drù be ne bla gi nje in vpli va na kako vost ìv lje nja pre bi val cev. To doka zu je jo tudi raz li~ ne mere gos po dar ske ga raz vo ja (Su hrc ke in osta - li 2006; Buze ti in osta li 2011, 17–28), v ka te rih se pojav lja ved no {ir {i nabor kazal ni kov zdrav ja. [e zla sti v lu ~i tre nut ne gos po dar ske kri ze lah ko na podro~ ju jav ne ga zdrav ja zasle di mo, da bo prob le ma ti ka du{ev - nih motenj v ~a su tra ja nja kri ze {e pose bej aktual na (WHO 2011). Novej {e med na rod ne in doma ~e razi ska ve namre~ è poro ~a jo o po ra stu samo mo ril ne ga in nasil ne ga vede nja, pove ~a ni zlo ra bi drog in alko ho la ter vi{ ji inci den ci depre siv nih in ank sioz nih motenj raz po lo è nja, ki jih med dru gim pove zu je jo tudi s splo - {no drù be no nego to vost jo, izgu ba mi zapo sli tev ter poglab lja njem social nih in eko nom skih raz lik med raz li~ ni mi pre bi vals tve ni mi sku pi na mi (Levy in Sidel 2009; Av~in in osta li 2011; Miku li}, Sándor in Leon - ci kas 2012). Zato bo pri bodo ~em na~r to va nju in izva ja nju social nih in zdravs tve nih poli tik potreb no poz na ti tudi regio nal ne raz li ke in z nji mi pove za ne kul tur ne raz li ke, sled nje ima jo velik vpliv na regio nal ni raz - voj (Ur banc, Boesch in Jelen 2007; Raz pot nik, Urbanc in Nared 2009). Le tako bomo sle di li ciljem raz li~ nih stra te{ kih usme ri tev za zago tav lja nje bla gi nje in zdrav ja vsem pre bi val cem Slo ve ni je. 5 Sklep V pris pev ku smo pred sta vi li razi ska vo bla gi nje v slo ven skih regi jah s po mo~ jo meto do lo gi je sestav lje nih kazal ni kov. Pri tem smo izha ja li iz meto do lo{ kih pri po ro ~il OECD, a vklju ~i li le objek tiv no mer lji ve kazalni - ke bla gi nje. Poseb no pozor nost smo name ni li podro~ ju bla gi nje, pove za ne z zdrav jem, kjer smo preu ~i li regio nal ne raz li ke na podro~ ju splo {ne ga, poklic ne ga in peri na tal ne ga zdrav ja, tve ga nih vedenj ter raz - po lò lji vo sti zdravs tve no social nih sto ri tev. Izsled ki razi ska ve raz kri va jo dokaj hete ro ge no sli ko bla gi nje v slo ven skih regi jah, saj se med neka te ri mi regi ja mi kaè jo pre cej{ nje raz li ke v raz vi to sti, v ìv ljenj skem stan dar du kot tudi na podro~ ju zdrav ja pre bi val cev. Izsto pa Osred nje slo ven ska regi ja kot regi ja z naj vi{ - jo rav ni jo bla gi nje. V za hod ni Slo ve ni ji pre vla du je jo regi je zmer no viso ke bla gi nje (Go ri{ ka, Obal no-kra{ ka in Gorenj ska regi ja), med tem ko vzhod ni del Slo ve ni je geo graf sko zao kro à jo regi je z naj nì ji mi ravn mi bla gi nje (Ko ro{ ka, Spod nje po sav ska, Pomur ska in Zasav ska regi ja).V pri ha ja jo ~em obdob ju sve tov ne kri - ze se bodo ver jet no raz li ke {e dodat no poglo bi le. Bla gi nja, pove za na z zdrav jem, je v slo ven skih regi jah pre cej raz li~ na. Ker je dobro zdrav je popu la ci - je pomemb no tako za zmanj {e va nje rev{ ~i ne kot za dol go ro~ ni raz voj drù be in dvi ga nje splo {ne bla gi nje v drù bi, je {e pose bej pomemb no, da drà va delu je v sme ri zmanj {e va nja raz lik med regi ja mi. Zato bo tre ba v bo do ~e pos ve ti ti ve~ pozor no sti geo graf sko raz ~le nje nim podat kom. Le poz na va nje regio nal nih poseb no sti bo omo go ~i lo u~in ko vi to na~r to va nje in izva ja nje ukre pov na podro~ ju eko nom skih, social - nih, okolj skih in zdravs tve nih poli tik. 6 Zah va la Pris pe vek je bil pri prav ljen v ok vi ru razi sko val ne ga pro gra ma Jezik, spo min in poli ti ke repre zen ta ci je (P6-0347), ki ga sofi nan ci ra Jav na agen ci ja za razi sko val no dejav nost Repub li ke Slo ve ni je (ARRS). 7 Lite ra tu ra Glej angle{ ki del pris pev ka. 87 88 Acta geographica Slovenica, 54-1, 2014, 89–100 SOME OLDER SOURCES FOR CROATIAN EXONYM ANALYSIS Ivana Crljenko Part of the map of Australia from the Geographical Atlas (1955) showing that many geographical names were domesticated then. Ivana Crljenko, Some older sources for Croatian exonym analysis Some older sources for Croatian exonym analysis DOI: http://dx.doi.org/10.3986/AGS54105 UDC: 91:811.163.42'373.21 COBISS: 1.01 ABSTRACT: The article introduces the review of some older sources in the Croatian language that might be useful for the Croatian exonym analysis, and may also refer to the exonym status it the context of the Croatian language development and geographers' indifference concerning that issue. Because of frequent changes in orthography, geographical names (as well as exonyms) have experienced different modifications, which can be followed through eight analyzed editions published during the period from 1880 to 1974. It was indicated that geography as a profession has greatly failed in serious research of exonyms. KEY WORDS: geographical names, exonyms, Croatian language, orthography, geography, Croatia The article was submitted for publication on December 4, 2012. ADDRESS: Ivana Crljenko, Ph. D. Leksikografski zavod Miroslav Krleà Frankopanska 26 10 000 Zagreb, Hrvatska E-mail: ivana.crljenkoalzmk.hr 90 Acta geographica Slovenica, 54-1, 2014 1 Introduction Avoiding the current discussions and dilemmas of the definition and division of endonym and exonym terms, by the term exonym in this article we refer to »the name that is used in a language for the geographical object that is situated outside the area in which the language is widely spoken (and most frequently has the offi- cial status), and the name itself is significantly different from its original, endonymic form used in the area where the object is situated (and/or in the area where this language has no official status)« (modified accord- ing to: Kadmon 2002, 2006; Woodman 2003; Kladnik 2007a, 2007b, 2007c, 2007d, 2009; Jordan 2007). Exonyms, which are also known by other terms such as domesticated or Croatized geographical names, together with the original geographical names of objects situated outside the Croatian speaking area belong to a wider group of geographical names that we can tentatively put under the common denominator of »foreign« geographical names (Kladnik 2007c, 23; in Croatian strana or tu|a geografska imena). The aim of this article is to make a review of some older sources for the Croatian exonym analysis, and also to pro- vide the insight into a broader context of the Croatian language development, especially its orthographic rules, as well as to trace the geographers' indifference concerning systematic exonymic research. The pur- pose of this article is to make the analyzed sources the basic groundwork for drafting the list of standardized Croatian exonyms. 2 The methodology The chronological approach and text analysis of the names mostly situated on the maps have been used in this research. Eight representative geographical sources, atlases and lexicons have been singled out. Similarly, Drago Kladnik has reviewed and examined Slovenian exonyms and the results have been pub- lished in his book Podoma~ena tuja zemljepisna imena v slovenskih atlasih sveta (»Adapted exonyms in Slovenian world atlases«, 2007b). Not only have the principal bibliographical data of every publication been introduced in the research process, but also the way of writing geographical names has been empha- sized, i.e. exonyms, emphasizing the representative examples and theirs singularities. Since the analyzed editions were published between the 1880s, when the first such books appeared in the Croatian language, and 1970s, when the mass production of atlases and similar books mostly based on the translation of for- eign books began to appear, this almost one century long period has been divided into four periods, depending on the temporarily dominant language politics. Apart from that, we follow the development of geography in Croatia, so we could attain the answer to the question why during this long period of time there were only few prominent Croatian geographers who very rarely addressed the issue of writ- ing and using the exonyms in their abundant professional work. 3 Crossing the centuries: 19th to 20th century The status of the Croatian language from the second half of the 19th century till World War I was char- acterized by the struggle of four philological schools (Pranjkovi}, 2009: 4). Contemporary orthographies mostly followed the tradition of the Zagreb philological school, which advocated the position that geo- graphical names should be written according to the etymological, i.e. morphological principle. The pivotal characteristic of that principle is that one should not write the phonemes that are actually spoken, but should keep the root (etymon) of the word. For example, Francuz – Francuzka (French – France), Norveànin – Norvèka (Norwegian – Norway), Englez – Englezka (Englishman – England) (Bari} et al. 2003, 28). The fol- lowers of the other school, named Vuk's school, issued Hrvatski pravopis (»Croatian Orthography«) written by Ivan Broz, which was an important one because it was advocating the idea of »Pi{i kako govori{!« (»Write as you speak!«: Internet 1). It was the first orthography in Croatia that became obligatory for all schools. It was based on the phonological principle, but in its usage there were no extremes. Due to the lack of orthographical unity it is no wonder that we can find the reflection of mixed orthographical rules in many sources produced in that period. The first analyzed source named Slike iz ob}ega zemljopisa (»The Images from General Geography«) was published in six volumes from 1888 to 1900. Nineteen European countries were described in great 91 Ivana Crljenko, Some older sources for Croatian exonym analysis Figure 1: Map of Switzerland from The Images from General Geography showing exonymic forms of geographical names for lakes. detail there. The books were written by Ivan Hoi} who addressed mostly geographical and historical themes in his professional career. Methodologically, Hoi} followed the contemporary German geographical school – »the classical school«, as we call it today (Hrvatska enciklopedija, vol. 4, 606; Hrvatski biografski leksikon, vol. 5, 603–604). The mentioned volumes were issued during the period that is considered very impor- tant for the development of Croatian geography, i.e. not long after its institutionalization on the Faculty of Philosophy in Zagreb in 1883. From that moment on the first voluminous books and geographical stud- ies about the Croatian land written by Croatian authors were being published (Feletar 1993, 6–11; Pepeonik 1996, 12–13; Maga{ 2006). Producing these six volumes with dominantly geographical themes in the Croatian language was therefore a very serious and important event in the first years after the foun- dation of geography as an institutionalized science. Concerning the topic of writing geographical names, Hoi} has very often used Croatized names, e.g. Francuzka (France), Spljet (Split), Marselj (Marseille), Portugalska (Portugal), Mletci (Venice), Izto~na Rumelija (East Rumelia), Genovezki zaliv (the Genoa Bay), Bielo more (the White Sea), Osiek (Osijek), Bukare{t (Bucharest), Budape{ta (Budapest), Bruselj (Brussels), Jermenija (Armenia), Bristolski kanao (the Bristol Channel). On the other hand, some geographical names for which we nowadays usually use Croatized, domesticated forms, were then written in the forms more similar to the original ones, e.g. Athena (orig- inally Athína , English Athens), the state of Algir (originally al-Jazā'ir, English Algeria), Oporto (originally and in English Porto) , Firenza (originally Firenze, English Florence). That is the outcome of a started but not yet finished process of geographical names domestication. However, concerning the fact that Hoi} applied a very courageous approach of domesticating many still unaccepted geographical names, we can consider his books one of the earliest comprehensive sources for the Croatian exonym analysis. 4 Between the two world wars During the period between 1918 and 1941 many Croatian writers were impressed by the new Yugoslav enthusiasm and therefore started writing in ekavian pronunciation, but most of them returned to ijeka- vian pronunciation at the beginning of the 1920s. As part of strong endeavors in unifying the Croatian and Serbian standard languages, Pravopis srpskohrvatskog jezika (»Serbo-Croatian Orthography«) by 92 Acta geographica Slovenica, 54-1, 2014 Aleksandar Beli} was officially introduced (Bari} et al. 2003, 34–35). In wider usage there was also Pravopisno uputstvo za sve osnovne, srednje i stru~ne {kole Kraljevine SHS (»Orthographical Instructions for all Primary, Secondary and Professional Schools in the Kingdom of Serbs, Croats and Slovenens«) issued in 1929, according to which the names should be written phonetically or originally, the latter in the cases where the pronunciation of names was very distinct from the original versions. However, the frequency of usage of the mentioned rules in practice is evident from the following sources. Leksikon Minerva – prakti~ni priru~nik za modernog ~ovjeka (»Minerva Lexicon – a Practical Handbook for a Modern Man«) was the second source we analyzed. In its preface the Lexicon is intro- duced as »… not only the first ours, but also generally the first lexicon in the Slavic South …« It was published in 1936. In 1583 pages the Lexicon contains 54 000 terms and 8 maps, 2297 illustrations and 38 tables. Due to a rather vague explanation of rules for writing geographical names, in the Lexicon we can find many variants of geographical names. For example, we can find country names such as: Nicaragua, Costarica, Colombija (Columbia), Chile, Bolivia, Uruguay, New Zealand, Romania, [panija (Spain), Abesinija (the Ethiopian Empire, Abyssinia) or Canada, from which we can conclude that some country names had already gained their Croatian form, while others had not. We can also notice different hybrids in the names of seas, oceans, channels, mountains or regions: Koralno more (the Coral Sea), Arafura more (the Arafura Sea), Tasman-more (the Tasman Sea), Banda-more (the Banda Sea), Bassov put (the Bass Strait), Cookov put (the Cook Strait), Hudson Bay, Tripolitanija (Tripolitania), Grǿ nland (Greenland), or Alaska, so it seems that many geographical names had not been totally Croatized yet. The result was the appearance of a sort of semi-Croatized mixed names that consisted of a translated appellative, and not translated proper names, i.e. left in their original form, such as: Barents-more (the Barents Sea), Timor-more (the Timor Sea), Ural-gorje (the Ural Mountains). The first comprehensive world atlas in the Croatian language, Minervin svjetski atlas (»Minerva's World Atlas«) was published in 1938. The editors were the geographers Filip Lukas and Nikola Per{i}. Filip Lukas was a geographer, but also historian and theologian. He was especially interested in geopolitics, and was Figure 2: On the map of Australia and Oceania from the Minerva's World Atlas we can notice semi-Croatized forms of some sea names. 93 Ivana Crljenko, Some older sources for Croatian exonym analysis Figure 3: In Minevra's World Atlas the process of exonymization partly overtook country names, which is seen on the example of South America. addressing the topics within economic, regional and political geography, as well as lexicography (Hrvatska enciklopedija, vol. 6, 680–681; Maga{ 2007, 157). Nikola Per{i} was practising both economic geography and demography (Maga{ 2007, 157). Both of them were professionally engaged in the period between the two world wars, when the number of published books dealing with geographical issues significantly increased. However, these books were mostly foreign ones. Only in the later years of that period some Croatian geo- graphers distinguished themselves from the others (Feletar 1993, 11–12; Pepeonik 1996, 13; Maga{ 2006). Minervin svjetski atlas includes 169 textual pages and 50 colored maps (i.e. 110 main and »auxiliary« maps); it offers an overview of the world on the eve of World War II. In the last pages of the book there is a very detailed and systematic geographical names index, which makes this atlas an extremely alluring source for the exonym analysis. Concerning writing exonyms, in the preface we can read: »A small number of names of large towns and rivers for which we have traditional domesticated names (such as: Be~ (Vienna, author's comment), Rim (Roma, author's comment), Mleci (Venice, author's comment), Rajna (the Rhine, author's comment), Laba (the Elbe, author's comment) and so on), are being left as they are, together with the original names in the parentheses, for example Be~ (Wien) .« Lukas and Per{i} pointed out that »… despite our best will, somewhere … we had to recede from some principles for many reasons, because the absolute consistency would often be unsuitable.« 5 Period of the ISC (1941–1945) As an opposition to the Yugoslav linguistic trends, whose main tendency was homogenization of the lan- guages during the period between the two world wars, in the period of the Independent State of Croatia (ISC) the old Croatian linguistic tradition and reimplementation of the orthography based on keeping the root of the word came into life again. This time the morphological principle was applied literally (Bari} et al. 2003, 35). Namely, the new government of the »usta{a« wanted to remove »… all Serbized words 94 Acta geographica Slovenica, 54-1, 2014 imposed between 1918 and 1941 …« (Samardìja 2008, 43). The most important document of the linguistic politics was Zakonska odredba o hrvatskom jeziku, o njegovoj ~isto}i i o pravopisu (»Legal Regulation of the Croatian Language, Its Purity and Orthography«; Samardìja 2008, 45). New Hrvatski pravopis (»Croatian Orthography«) by the authors Franjo Cipra and Adolf Bratoljub Klai} was also written in 1944. The reference source for this period was Poviestni zemljopis Evrope (»A Historical Geography of Europe«). It is a translation of the original An Historical Geography of Europe by the author Gordon East published in 1944, with the index of geographical names in the end of the book. It is one of the oldest translated books of historical and political geography. Since there is a considerable lack of maps in the book, geographical names mainly appear in the textual part. It was noticed that the exonymic forms of the names were used in large extent, such as: Kampanja (Campania), Tiber (the Tiber), Eufrat (the Euphrates), Andaluzija (Andalusia), Galipolje (Gallipoli), Ma|arska (Hungary), Bavarija (Bavaria), @enevsko jezero (Lake Geneva), Daleki Iztok (the Far East), Englezka (England), Flandrija (Flanders), Katalonija (Catalonia), Solun (Thessaloniki), [lezija (Silesia), but we can also find semi-Croatized names such as Macedonija (Macedonia) or Toscana (and Toskana; Tuscany). Since the root based orthography was being literally applied, many geographical names from this source look very archaic from today's viewpoint, e.g. Englezka (modern Engleska; England), Francuzka (modern Francuska; France), Norvèka (modern Norve{ka; Norway). 6 After World War II After reaching the so called »Novi Sad Agreement« in 1954, the Croatian language became equal and unit- ed with the Serbian and Montenegrin languages (Bari} et al. 2003, 35). A mutual orthography was issued in 1960, based on the phonological principle according to Pravopis hrvatskosrpskoga knjièvnog jezika (»Orthography of the Serbo-Croatian Standard Language«) from 1958. Conceived in this way, the unity of language, together with the »Novi Sad Agreement« and new orthog- raphy, were rejected by the »Declaration on Language« (full name »The Declaration on the Status and Name of the Croatian Standard Language«) from 1967, the outcome of which was the appearance of Hrvatski pravopis (»Croatian Orthography«) by the authors Stjepan Babi}, Boìdar Finka and Milan Mogu{ in 1971. Besides some others, we have used this orthography handbook till today. Although it especially accentu- ates the problems of writing exonyms, its main disadvantage is that while explaining the ways of writing exonyms, there are just a few examples for it, and those are generally the uncontested ones. For instance, on page 69 of the 1994 edition as the examples of region names and country names there are: Albanija (Albania), Austrija (Austria), Bavarska (Bavaria), Bugarska (Bulgaria), ^e{ka (the Czech Republic), Danska (Denmark), Engleska (England), Etiopija (Ethiopia), Gr~ka (Greece), Indija (India), Irska (Ireland) … while disputable names such as Kapverdski Otoci (Cape Verde), Maldivi (the Maldives), Mijanmar (Myanmar) are not even mentioned, which leaves room for arbitrary interpretations of writing geographical names that are not given in the book (Crljenko, Klemen~i} 2011, 108). In the analysis, this period is primarily represented by Geografski atlas i statisti~ko-geografski pregled svijeta (»Geographical Atlas and Statistical-Geographical Overview of the World«). We have analyzed its fourth edition from 1955; the first edition was issued in 1951. The editors were Petar Marde{i} and Zvonimir Duga~ki, while the technical editor of the maps was Josip Zori~i}. Petar Marde{i} was a sailor, lexicogra- pher, cartographer and publisher. He was a contributor to the Pomorska enciklopedija (»Naval Encyclopaedia«), and also the editor-in-chef of many atlases published by the Lexicographical Institute (Hrvatska encik- lopedija, vol. 7., 58; Maga{ 2007, 158). Prior to all his interests, Zvonimir Duga~ki was a geographer and cartographer. He was addressing the themes within the anthropogeography and regional geography and was also an author of many geographical and historical school maps (Hrvatska enciklopedija, vol. 3, 292; Hrvatski biografski leksikon, vol. 3, 659–660; Maga{ 2007, 157). The productive scientific and professional work of both editors was accomplished in the period of a serious consolidation in the organization of Croatian geography, i.e. its actual shifting to the Faculty of Science. By doing so, new, more favorable con- ditions for its literature enrichment appeared (Feletar 1993, 12–16; Pepeonik 1996, 13–17; Maga{ 2006). Apart from that, the Lexicographical Institute of the Federal People's Republic of Yugoslavia was estab- lished in 1950, which made a stable foundation for a serious scientific and professional lexicographical work based on the merits. Besides Marde{i} and Duga~ki, some other prominent geographers were also permanent contributors with the Institute, such as: Oto Oppitz, Josip Rogli}, Ivan Rubi}, Veljko Rogi}. 95 Ivana Crljenko, Some older sources for Croatian exonym analysis Figure 4: Map of Central Europe in the Geographical Atlas and Statistical-Geographical Overview of the World showing the unequal status of domesticated town names in respect to the original names. In their lexicographical work they all surely had to address the problems of writing exonyms. Therefore since then geographers started to think of exonyms as a serious topic, at least of the issues concerning their usage on maps and in texts. Geografski atlas i statisti~ko-geografski pregled svijeta includes 50 colored general geographical maps and an alphabetical index of geographical names in the end of the book. By comparing the maps, it was observed that in some cases geographical names were written exclusively in their exonymic forms, such as Prag (Prague), Be~ (Vienna), Budimpe{ta (Budapest), while in some other cases both forms were used, e.g. Atene (Athinai; Athens), Rim (Roma; Rome), Praha (Prag; Prague), Warszawa (Var{ava; Warsaw). Such a situation gives us the right to imply that the makers of the maps had many difficulties in the implementation of rules for writing geographical names in practice. Nevertheless, exonyms began to be used in larger extent than before. For example, Kalifornija (California) was written in its exonymic form back then, so that it could later be written as California, and again Kalifornija. On the map of the United States of America, on the other hand, we could find rendered names for Jùna (South) and Sjeverna Karolina (North Carolina), but also Texas and New Mexico, and a mixed name between an endonym and a full exonym Virginija (Virginia). As opposed to the still disputable names of regions, federal states and towns, the names of seas and bays gained their full adjectival forms. The next examined source was Enciklopedija Leksikografskog zavoda (»Encyclopaedia of the Lexico- graphical Institute«). For the purpose of this analysis we have reviewed its first edition, which was published in seven volumes between 1955 and 1964. Two longtime Institute associates were involved in the process of making this Encyclopaedia, Oto Oppitz and Veljko Rogi}, as the chief geographical editors. Oto Oppitz was a geographer and lexicographer, a physical geographer by vocation. He was also a permanent con- tributor and editor in many geographical and cartographical editions published by the Institute, such as Pomorska enciklopedija (Hrvatska enciklopedija, vol. 8, 112).Veljko Rogi} is a geographer whose interests are mostly connected with regional, historical and political geography (Hrvatska enciklopedija, vol. 9, 396; Maga{ 2007, 185). 96 Acta geographica Slovenica, 54-1, 2014 The analysis of exonyms showed that most hydronyms and some (but not all!) names of regions were Croatized, for example Australian federal states Novi Jùni Wales (New South Wales) and Zapadna Australija (Western Australia). A portion of the Croatized geographical names in Enciklopedija, similarly as in the other Institute's editions issued in the 1950s and 1960s, can be considered very remarkable compared to the pub- lications that followed. Whether intuitively, whether because of the general internationalization and therefore increased necessity for the endonym use, and probably under the influence of a better familiarity of map makers with the global trends in the development of the exonym idea (especially concerning the 29th res- olution of the Second UN Conference on the Standardization of Geographical Names held in 1972; Internet 2), a portion of exonyms in the following editions considerably decreased. Oto Oppitz and Petar Marde{i} were the chief editors of the first edition of Atlas svijeta (»World Atlas«) published by the Lexicographical Institute of the Federal People's Republic of Yugoslavia in 1961. There are 200 pages of geographical maps and an index that includes about 51 000 geographical names in the end of the book. The exonym analysis in Atlas svijeta implicated that exonyms were used in a large extent. When being the oikonyms, exonyms had an advantage over the endonyms, so they were written on the place with larg- er fonts and then the endonyms followed, written in the parentheses in smaller fonts, e.g. Be~ (Wien; Vienna ), Budimpe{ta (Budapest), Prag (Praha; Prague). This kind of practice was abandoned later, so in the latest edition (7th edition) the practice is reversed. The last reviewed source was Veliki atlas svijeta (»Great World Atlas«), which was issued in 1974 as both Slovene and Croatian (Serbian) volume. The editor-in-chief for the Croatian edition was a geogra- pher, author and editor of the school literature and atlases Alfonso Cvitanovi} (Hrvatski biografski leksikon, vol. 2, 773–774). Veliki atlas svijeta offers the abundance of general geographical maps and thematic maps, as well as a textual and tabular appendix for the entire world, continents, parts of the world and coun- tries. The book ends with an index of geographical names. A whole chapter in the Atlas, the one between pages 392 and 399, is devoted to geographical names, which was not the case before. In that chapter the editor explains the major problems of writing and read- ing geographical names in great detail. That is the reason why this text might be considered as one of the most Figure 5: Domesticated names of seas, bays, islands and mountains on the map of North America in the World Atlas. 97 Ivana Crljenko, Some older sources for Croatian exonym analysis influential texts about the aforementioned topic. Not only does he argue the key dilemma of the map and atlas makers (whether to adopt the original name, and if so which one, or to accept the name that is domes- ticated), but he also refers to the international practice of treatment of geographical names, and emphasizes the problems of inconsistent writing of geographical names, the problems that are discussed even today (see more in: Crljenko 2008). The latter is the result of an absence of scientifically embedded body that would be engaged in the issues of geographical nomenclature (Cvitanovi}'s criticism was initiated in 1974!) (see more in: Fari~i} 2003; Crljenko 2008). In the exonym-endonym relation he gives priority to endonyms (on maps the exonyms are written in the parentheses, e.g. Roma (Rim; Rome), Napoli (Napulj; Naples), Trieste (Trst)). Cvitanovi} also accentuates the problem of inconsistency of our orthography (he was using Pravopis hrvatskog knjièvnog jezika (»Orthography of the Croatian Standard Language« from 1960), the problem that is being alerted to even today (Crljenko 2012). The insight into the mentioned orthography hand- book makes him wonder: »… why should we exclude šonly domesticated names such as Prag (Prague, author's comment), Var{ava , (Warsaw, author's comment), Poznanj (Poznan, author's comment), Laba (the Elbe, author's comment), Odra (the Oder, author's comment) and so on’? … Why should we render the name Teutobur{ka {uma (the Teutoburg Forest, author's comment), and use an untranslated name Schwarzwald? … In such cases the explanation that šthese names were adapted to our language ages ago’, which we can find in the orthog- raphy book, does not help.« 7 Key observations on the exonyms in the analyzed editions According to the analysis of the chosen sources and by comparing the status of exonyms, its characteris- tics and the manners of writing and its usage, we have reached the following observations: • The way of writing and the usage of exonyms are usually prescribed by the orthography rules, so as these rules changed, the characteristics of the foreign geographical names changed, too. The Croatian language and its orthography, as well as its exonyms, have been influenced by the political situation too often. • The examples introduced in the orthography are very seldom and they are almost always the uncon- tested ones, so it often seems that there is no point in bringing up the rules for writing the geographical names at all. There are too many geographical names the writing of which stays unclear even after con- sulting the orthography. • The earlier orthographies, prefaces or introductory chapters in the analyzed editions paid little atten- tion to the explanations regarding writing foreign geographical names. When the practice improved, the writing became somewhat more uniformed. • Between the two world wars sorts of mixed names between exonyms and endonyms appeared, i.e. semi-Croatized hybrid forms, especially hydronyms, which later adopted the full exonymic forms by translation or adjectival adaptation. • Inconsistency noticed on the maps and in the texts inside the same publication is the result not only of abundance of geographical names, but also of both unclear treatment and the manners of writing geo- graphical names. This was usually the case in the periods of transition from the original to the exonymic form of the names (e.g. in the oldest analyzed sources), especially after passing a resolution about reduc- ing the number of exonyms, after which geographical names started to adopt their original forms again. • Depending on the form the priority is given to (earlier to exonyms, later to endonyms), in some sources exonyms are written as the heading entries in the text or in the first place on the maps, while endonyms are written in the parentheses. In other sources, usually the newer ones, it is vice versa. • The exonyms that have existed in the Croatian language for a long time and have therefore become part of our everyday communication, such as Be~ (Vienna), Budimpe{ta (Budapest) or Trst (Trieste), appear in their exonymic form in all analyzed sources, no matter where they stand. Troubles arise with the exonyms that were not totally domesticated by the time of the publication of the mentioned sources, such as Teksas (Texas), Sjeverna Dakota (North Dakota), Jùna Australija (South Australia), [angaj (Shanghai) and so on. Therefore we can find them written in both ways. • The review of geographical names in all examined editions indicated that the stage of exonymization depends on the type of geographical feature, so country names have become totally domesticated with time, while the names of towns and territorial units have been Croatized to a much lower extent. The names of seas, bays, rivers and so on have also been partially domesticated, often by translation or by using adjec- tival forms. However, there are many exceptions that we cannot understand. 98 Acta geographica Slovenica, 54-1, 2014 8 Conclusion When and if the problem of writing exonyms is discussed in Croatia, it is usually not about when to use an exonym and/or an endonym, but how to write one and why we cannot find it written in the same way in all of literature. The problems that arise from inconsistent and non-standardized writing of exonyms are indeed widespread in Croatia (Crljenko 2008), although many other languages have to deal with sim- ilar issues as well (Kladnik 2005; Kladnik an Bole). Such a chaotic situation in which one cannot be sure how to write a specific Croatized geographical name (and whether to domesticate an original name in the first place), seems to be a direct outcome of the deficiency of the orthographical rules, as well as the absence of a unique standardized list of exonyms. The latter one is the result of the absence of a commission that would seriously and frequently be engaged in the subject matter of geographical names, not just the prob- lems with exonyms. Analyzing the treatment, form and use of geographical names (and exonyms) in the chosen sources, we can say that geographical names have been significantly influenced by the development of the Croatian language. Though geographical names, as well as exonyms, should undoubtedly be examined and ana- lyzed from the interdisciplinary point of view of several sciences, »… in Croatia those are (exonyms, author's comment) almost exclusively treated as an orthographical problem …« (Brozovi} Ron~evi} 2011). Considering the obvious and indisputably strong relationship between language, orthography and geographical name, it is no wonder that Croatian linguists have gone furthest in the studies of geographical names. From 2005 to 2012 they were assembled in Vije}e za normu hrvatskoga standardnog jezika (»Council for the Standard Croatian Language Norm«), with the aim of standardizing language, geographical names, too (Brozovi} Ron~evi} 2011). The process of exonym standardization has gone furthest in exonymization of country names and dependent territories, so on the official level Abecedni popis dràva i zemalja i njihovih ozna- ka (»Alphabetical list of countries and territories and their markings«; Internet 3) is being used. To a much lesser extent, if at all, the use and treatment of geographical names have been influenced by the development of Croatian geography, which should certainly have a more important role regard- ing toponymy. Unfortunately, geographers have not been systematically analyzing and systematizing geographical names so far. All geographers mentioned in this article mainly brought to consciousness the problems of writing geographical names at the time they were involved in the lexicographical work. Apart from rare exceptions, the enthusiasm of other geographers concerning this topic has been even less- er. Certainly, that does not mean that geographers are unaware of the problems that arise in writing and pronunciation of exonyms. Nevertheless, it seems that the topic is not very challenging for them, or they think they have too little to say about it (which cannot be more wrong!), or they are simply oriented to other, »more geographical« themes. We will see if this kind of disinterest in the problems of geographi- cal names among the Croatian geographers will soon be changed. 9 References Atlas svijeta. Leksikografski zavod FNRJ Zagreb, 1961. Babi}, S., Finka, B., Mogu{, M. 1971, 1994: Hrvatski pravopis. Zagreb. Bari}, E., Lon~ari}, M., Mali}, D., Pave{i}, S., Peti, M., Ze~evi}, V., Znika, M. 2003: Hrvatska gramatika. Zagreb. Broz, I. 1892: Hrvatski pravopis. Zagreb. Brozovi} Ron~evi}, D. 2011: Exonyms as a reflection of cultural heritage. The twentieth session of the East Central and South-East Europe division of the UNGEGN. Zagreb, 9–11. 2. 2011. Internet: http://ungegn.dgu.hr/ungegn20/27_CRO_ECSEED_Documets_Brozovic_Exonyms.pdf (12. 11. 2012). Cipra, F., Klai}, A. B. 1944: Hrvatski pravopis (uz suradnju ~lanova Ureda za hrvatski jezik). Zagreb. Crljenko, I. 2008: O pisanju geografskih imena: Neke nedoumice u hrvatskim leksikografskim i kartografskim djelima. Studia lexicographica 1-2. Crljenko, I. 2012: Geographical feature importance as a criterion for exonym selection: Croatian Examples. The great toponymyc divide. Warszawa. Crljenko, I., Klemen~i}, M. 2011: Geografska imena u leksikografskim izdanjima. Zbornik radova Prvog nacionalnog znanstvenog savjetovanja o geografskim imenima. Zadar. 99 Ivana Crljenko, Some older sources for Croatian exonym analysis East W. G. 1944: An historical geography of Europe. Zagreb. Enciklopedija Leksikografskog zavoda 7. Zagreb, 1955–1964. Fari~i}, J. 2003: Je li u Hrvatskoj potrebno povjerenstvo za geografska imena? Internet: http:/ www.geografija.hr/ clanci/60/je-li-hrvatskoj-potrebno-povjerenstvo-zageografska imena (14. 10. 2003). Feletar, D. 1993: Pregled razvoja geografije u Hrvatskoj – uz 110. obljetnicu katedre za geografiju u Zagrebu. Acta geographica Croatica 28. Geografski atlas i statisti~ko~-geografski pregled svijeta. Selja~ka sloga. Zagreb, 1955. Glossary of Terms for the Standardization of Geographical Names. UNGEGN, United Nations Publication. New York, 2002. Hoi}, I. 1888–1900: Slike iz ob}ega zemljopisa 1–5. Zagreb. Hrvatska enciklopedija, sv. 3, 4, 6, 7, 8, 9. Zagreb, 2001, 2002, 2004, 2005, 2006, 2007. Hrvatski biografski leksikon 2, 3, 5. Zagreb, 1989, 1993, 2002. Internet 1: http://webograd.tportal.hr/Miha29/hrvatskijezik/kratkapovijesthrvatskogajezika (12. 11. 2012). Internet 2: http://unstats.un.org/unsd/geoinfo/ungegn/docs/2nd-uncsgndocs/e_conf_61_4_en.pdf (13. 9. 2012). Internet 3: http://www.nn.hr/clanci/sluzbeno/1994/0840.htm, http://www.nn.hr/clanci/sluzbeno/2001/ 1840.htm (20. 11. 2012). Jordan, P. 2007: Considerations on the definitions of »endonym« and »exonym«. Exonyms and the inter- national standardisation of geographical names. Wien. Kadmon, N. 2006: Exonyms, also called conventional names. Manual for the national standardization of geographical names. New York. Kladnik, D. 2005: Geografov pogled na tuja zemljepisna imena v Slovenskem pravopisu 2001. Geografski vestnik 77-2. Kladnik, D. 2007a: Characteristics of Exonym Use in Selected European Languages. Acta Geographica Slovenica 47-2. DOI: http://www.dx.doi.org/10.3986/AGS47203 Kladnik, D. 2007b: Podoma~ena tuja zemljepisna imena v slovenskih atlasih sveta. Geografija Slovenije 14. Ljubljana. Kladnik, D. 2007c: Pogledi na podoma~evanje tujih zemljepisnih imen. Georitem 2. Ljubljana. Kladnik, D. 2007d: Prispevek k poenotenju rabe podoma~enih tujih zemljepisnih imen v slovenskem jeziku. Geodetski vestnik 51-3. Kladnik, D. 2009: Semantic Demarcation of the Concepts of Endonym and Exonym. Acta Geographica Slovenica 49-2: DOI: http://dx.doi.org/10.3986/AGS49206 Kladnik, D., Bole, D. 2012: The life of Slovenian exonyms and their familiarity in the professional com- munity. Acta geographica Slovenica 52-2. DOI: http://dx.doi.org/10.3986/AGS52204 Leksikon Minerva – prakti~ni priru~nik za modernog ~ovjeka. Zagreb, 1936. Maga{, D. 2006: Kratak prikaz razvoja hrvatske geografije. Internet: http://www.geografija.hr/clanci/977/ kratak-prikaz-razvoja-hrvatske-geografije (6. 11. 2006). Maga{, D. 2007: Geografija i geografi na visoko{kolskim ustanovama u Hrvatskoj izvan Prirodoslovno- matemati~kog fakulteta u Zagrebu. Geoadria 12-2. Minervin svjetski atlas. Minerva nakladna knjiàra d. d., Zagreb, 1938. Pepeonik, Z. 1996: Razvoj geografije u Hrvatskoj od njene institucionalizacije do danas. Zbornik radova Prvog hrvatskog geografskog kongresa. Zagreb. Pranjkovi}, I. 2009: Hrvatski jezik u 19. st. Internet: http://www.hrvatskiplus.org/prilozi/dokumenti/ anagram/Pranjkovic_Hrvatski.pdf (12. 9. 2012). Pravopisna komisija: Pravopis hrvatskosrpskoga knjièvnog jezika. Zagreb, 1958. Pravopisno uputstvo za sve osnovne, srednje i stru~ne {kole Kraljevine SHS s kratkim tuma~enjem i obja{njenjem. Zagreb, 1929. Samardìja, M. 2008: Hrvatski jezik, pravopis i jezi~na politika u NDH. Zagreb. Veliki atlas svijeta. Prosveta i Mladinska knjiga. Beograd, Ljubljana, 1974. Woodman, P. 2003: The UNGEGN Definitions of »Endonym« and »Exonym«. Working Group on Exonyms. Prague. Internet: http:/ www.zrcsazu.si/wge/Documents/Papers%20Prague/Woodman_Exonyms%201.pdf (25. 3. 2008). 100 Acta geographica Slovenica, 54-1, 2014, 101–113 A GEOGRAPHICAL METHODOLOGY FOR ASSESSING NODALITY OF A ROAD NETWORK. CASE STUDY ON THE WESTERN MOLDAVIA Daniel Tudora, Mihail Eva ARODU TLIENAD Road network is an important landscape element. Daniel Tudora, Mihail Eva, A geographical methodology for assessing nodality of a road network. Case study on the western Moldavia A geographical methodology for assessing nodality of a road network. Case study on the western Moldavia DOI: http://dx.doi.org/10.3986/AGS54107 UDC: 911.3:656(478) COBISS: 1.01 ABSTRACT: The study tests the concept of nodality in a three-dimensional space, both as a projection of the physical-geographical support and an expression of topological centrality, which is insufficiently employed in papers attempting to evaluate the geographical or potential accessibility. The junctions of the reticular systems will be positioned differently within the network depending on the acquired nodal- ity values, which may influence through their importance the potential for development of the polarized territory. By focusing on a methodology specific to nomothetic epistemology, aimed at highlighting the vul- nerabilities induced by the dysfunctions within the road network and obtaining nodal hierarchies, the study allows for the extraction of legitimate relationships, which can be extrapolated beyond the particular space matrix selected for demonstration purposes only. KEY WORDS: geography, transport geography, impeded-distance, accessibility, centrality, reticularity, roughness, Moldavia The article was submitted for publication on November 13, 2013. ADDRESSES: Daniel Tudora, Ph. D. Department of Geography, Faculty of Geography and Geology University »Alexandru Ioan Cuza« of Iasi Carol I Blv. 20A, 700505 Iasi, Romania E-mail: tudoradanielayahoo.com Mihail Eva Department of Geography, Faculty of Geography and Geology University »Alexandru Ioan Cuza« of Iasi Carol I Blv. 20A, 700505 Iasi, Romania E-mail: e_mihailayahoo.com 102 Acta geographica Slovenica, 54-1, 2014 1 Introduction The concept of nodality, as it is used in the field of Transport Geography, refers to a set of properties that a place (defined geometrically as a point) fulfils a geographical network. Furthermore, from the perspective of graph theory, any point benefits from its own nodality, with the implicit condition that the graph is connected. From these perspectives, the concept was constantly approached by geographers (see for exam- ple Ducruet 2008 for the field of transportion geography; Matthiessen et al. 2006 and 2002 for urban geography), but in the case of synthetic works in the field, it is either avoided, either given a secondary impor- tance. Thus, from six reference works in geography of transportation, published over the last two decades (Rodrigue et al. 2009; Knowles et al. 2008; Black 2003; Banister 2002; Taaffe et al. 1996; Mérenne 1995), none is explicitly presenting the importance of indicators of nodality for geographical studies. Furthermore, the term of nodality is rarely used, no more than twice per piece of work. The study of nodalities in the field of transportation geography is even more important since in the actu- al context of globalisation and dilution of national borders, permanent repositioning and redefinition of nodal points occur. As Knowles simply puts it, » nodal situations change and the spatial qualities of cen- trality and intermediacy enhance the importance of strategically located hubs« (Knowles 2006). Furthermore, the nodality is subject to trans-scalarity, its values being significantly different depending on the scale of analysis (see Debrie et al. 2005 for an example on the port nodalities). Capital City Borderline 1 3 The historical region of Moldavia 2 1 Northwestern Moldavia (Bukovina) 4 2 Western Moldavia Bucharest 3 Eastern Moldavia (Bassarabia) lack Sea B 4 Southeastern Moldavia (Budjak) R 0 30 km rea U k r a i n e e p. y A 29 o d f tu 2 M S o 29 2 l 4 d C a 17 2 v E 2 i a Main cities (inh.) Iași 15B 320.000 15 County roads 24 2 National roads Bacău 15B The name of the National Road (NR) 24 2 Altitude (m) 24 Author of contents/avtor vsebine: Tudora D., Eva M. 0–200 Author of map/avtorica zemljevida: Tudora D., Eva M. 201–800 Source/vir: Topographic Maps of Romania – 1:50.000, 2 Galați Military Topographic Department; Earth Remote Sensing 801–2,057 Data Analysis Centre, Japan. © University »Alexandru Ioan Cuza« of Iași, 2012 Figure 1: The study area as part of the historical region of Moldavia. 103 Daniel Tudora, Mihail Eva, A geographical methodology for assessing nodality of a road network. Case study on the western Moldavia In this regard, the present article proposes a trans-scalar methodology for assessing nodality with the pur- pose of determining incoherences and vulnerabilities of a given reticular space. Nodality is seen as an internal feature of the reticular system, not to be confused with centrality and intermediacy as defined by Fleming and Hayuth (1994). The present article takes nodality as a property assigned initially only to the junctions of the network, but then transfers it through proximity and spatial interaction rules to neighbouring areas, taking into consideration the morphological aspects of the network (including the influence of topog- raphy) and the demographical aspects of settlements. In the three-dimensional reticular environments, the space allows the interpreter to identify the fric- tion that topography imprints on the network communication paths. The new topological context has the advantage of extracting, beyond the rigidity of a flat/predictable surface, the roughness with which the phys- ical-geographical parameters lead to the occurrence rhythm rupture inside the network. Therefore, spaces select and are differentially selected, depending on certain features of cost and efficiency, the ability to reach them and from them being disturbed by the difficulty with which they manage to put in place fast routes, regardless of topography imperfections. The intensity and the frequency through which the sup- port-environment creates and transfers geographical determinism produce disabilities within the routes communication systems, generating vulnerability to it. A vulnerable system of communication routes always involves additional costs in terms of time, waiting, or other costs resulting from delays or deviations (see Berdica 2002 for an overview). From a geographical point of view, the evolution of the vulnerability of a net- work, combined with the low resilience of socio-spatial systems including them, produces various forms of risk: isolation / claustration, disconnection / decoupling, divergence / territorial fragmentation. The support-testing region for the hypothesis was chosen for having a common evolution of the net- work of communication routes. The eight Romanian counties included in the study area, with a surface of 46,000 km2 and a total population of 4.7 million at the last census, represent nowadays a part of the his- torical region of Moldavia integrated into the Romanian territory since the formation of the modern Romanian state in the mid-nineteenth century (see Muntele et al. 2009 for an overview). The only excep- tion is represented by the South Bukovina, a 5,000 km2 area annexed to Romania after the First World War (figure 1). 2 Methodology Peculiarities of the road network in Moldavia will be highlighted through the synthesis of methods spe- cific to the analysis of reticular, planiform, and punctiform space structures. Since the ultimate goal of the study is to obtain models of functionality in the network, final products of the research will have several utili- ties. They are as follows: assessing / quantifying the role of physical-geographical factor in the deterioration of connectivity indices, extraction of the points with high nodality and identifying the dysfunctional ones, and posting a graphic synopsis underpinning the optimization models of connectivity. To obtain the final models the three steps will be followed (figure 2): a) Road network in Moldavia will be transformed into a graph in which vertexes will be represented by the junction of county and national roads. This yields to 1,240 road segments (arcs) and 881 junctions (nodes). The length of segments will be weighted by two parameters: sinuosity and slope. In this way, the obtained graph becomes a weighted graph, measured by an impeded-distance that expands or contracts space depending on the specific roughness. b) Network centrality to the settlement systems of the region will be evaluated based on the potential inter- action between area of influence of the graph nodes and the demographic barycentres of each reference system (natural, micro-regional, and regional). Distance parameters will use the distance-impedance deter- mined in the previous step. Through this process, three types of adjusted nodality will be obtained: at the over-local, micro-regional, and regional level. c) Total nodality for each junction will be calculated by means of progressive/ trans-scaling aggregation between the three types of adjusted nodality, where the natural nodality has the highest share. The nodal hierarchy of road segments within the network will be calculated as the arithmetic mean between the nodal values that load each junction and the determination of vulnerabilities of the reticular space of Moldavia will be extracted through a multivariate analysis. For the calculations and the spatial analysis we made use of ArcGIS 9.3. 104 Acta geographica Slovenica, 54-1, 2014 Digitizing the county and national Dividing roads into segments using the junctions of the network roads Identifying the junctions Dividing segments into Calculating real equal to each other distamce for each Y sub-segments R road segment (d) S Calculating the gross nodality for (200 m long) A I each junction N S I YL M Identifying nodal polarization areas I A L by calculating the interaction N E potential of localities with the gross Calculating the slope (p) Calculating the sinuosity (s) A R nodality value of junctions P Calculating the demographical 1+p size for each junction (Pj) Calculating impeded-distance Di=(1+s) d * Delimiting Analysis at the Calculating demographical Calculating the adjusted R conventional barycentres and the number nodality at the over-local A over-local level hydrographical basins L S of population polarized (Pbb) level Nab=(Pj x Pbb)/Di 2 I A S Using county C Y Analysis at the Calculating demographical Calculating the adjusted S L administrative - county level barycentres and the number nodality at the county level S A limits of population polarized (Pcb) Nac=(Pjc x Pcb)/Di2 N N Analysis at the Calculating demographical Calculating the adjusted A A regional level barycentres and the number nodality at the regional level R 2 T of population polarized (Prb) Nar=(Pjr x Prb)/Di Total nodality calculated by successive aggregation of the adjusted nodalities: S Nf = Nab + Nac Nab + Nar Nac Nab T * * * L US The importance of road segments ER The typology of nodal spaces according to the average of segments importance Figure 2: Guideline on the methodology for identifying the spatial structures generated by nodality. 3 Preliminary analysis Connecting lines within a graph created by road network should be seen in their value dimension, actu- ally representing distances/expressions of the spatial cost. Distances can be expressed in metric, temporal or cost dimensions, each with its own advantages and disadvantages (see Curl et. al. 2011 for an overview). Using metric distances seems obsolete since the new GIS technologies makes possible to calculate, with a relatively high precision, the temporal distances (Berke and Shi 2009; Salonen et al.; Shaw 2006) or the eco- nomic ones (cf. Combes and Lafourcade 2005). The latter are however dependent on the technological or economic conditions of the moment, reason for being susceptible to contextual changes. What appears to remain a permanent constraint for a more efficient functioning of the road network are its physical characteristics (sinuosity, slope), dependent on both the level of engineering techniques, but especially on the indirect influence of topography (especially for developing countries). 3.1 Assessing the influence of the topographic support Although often positively correlated, roughness and altitude are different characteristics of land surface, the first with a spatial distribution that does not require uniformity, regularity and hard to comply with the inferential laws. 105 Daniel Tudora, Mihail Eva, A geographical methodology for assessing nodality of a road network. Case study on the western Moldavia In reality, the roughness is a problem of topography, being an indicator strongly correlated with the ter- rain slope and its aspect (Sappington et al. 2007). In order to evaluate this two dimensions of roughness and the influence it has on the road network, we made use of two indictors: a first one calculating the slope (altitude variation between two points in relation with the distance separating them), and a second one estimating the degree of route collinearity, i.e. the sinuosity. Both indicators were estimated using topographic maps 1 : 50,000 (for digitizing the road network) and a Digital Elevation Model with a 30 meters resolution provided by Earth Remote Sensing Data Analysis Centre (for extracting the altitudinal values), which were considered satisfactory for calculating the sin- uosity (using the Linear Proprieties ArcScript provided by Rathert 2003), but insufficient for the slope parameter. To correct deficiencies in the slope case (common in mountains due to the presence of numer- ous road segments that traverse areas with slopes with packed walls or with reinforced embankment), one should use a raster with a very fine resolution, close to the actual width of the road (6 m for the carriageway and about 8 m for all parts of the platform). Through the synthesis of the two variables of roughness, the space transmits to the network a certain friction, felt in each segment as a resistance force of the natural support, called impedance, and the asso- ciated distance will be named impeded-distance ( D ): i D (1 s)⋅ d + 1 p = + (1) i n ∑ H ∆ p i = =1 (2) d e s = 1− (3) d where D is the impeded-distance, s – the sinuosity, d – the metric length of the road segment, p – the slope, i Δ H – the maximum difference in altitude of each road sub-segment 200 m long, and e – the Euclidean distance between the ends of the road segment. From the formula (1), one can notice that each variable has a different impact factor: sinuosity is related to the distance by a multiplicative function, while the slope by an exponential one (friction imposed by a unit increase in the slope is greater than for a unit increase of sinuosity). The roughness becomes an indicator able to quantify the heterogeneity of physical support and simul- taneously to capture the impedance imposed on communication routes by altitude, landform energy, and topographic fragmentation. Joining an impedance ratio leads to obtaining an impeded-distance always greater or equal to the dis- tance actually measured, so it can be used later to calculate other types of geographical distance: time-distance, cost-distance, or economic-distance. Calculating the percentage ratio between impeded-distance and Euclidian distance, one can estimate the share of landform factor affecting distances between points, axes, and areas (figure 3). The network of major roads of communication in Moldavia remains faithful to the conditions imposed by the topography roughness; thereby the network connectivity is vitiated by undue preference for S–N or NW–SE coupling direction. Deficiencies on the east–west connectivity are not mitigated by technical engineering innovations designed to reduce the roughness of the landform. 3.2 Assessing the gross nodality Irrespective of the scale of analysis, the roads network creates junctions, which, depending on the prox- imity between them, will provide the associated spaces with the probability of interacting on various directions and configurations. As this probability is ensured easier, the administered reticular sub-systems will have a higher connectivity, will become more accessible, will stimulate emissions and attractiveness, will generate centres; hence, they will dispose of nodality. The nodality is the potential the network provides to the territory, in order to blend the real accessibility, to correct the centrality, and to generate anisotropic spaces. 106 Acta geographica Slovenica, 54-1, 2014 0 30 km U k r a i n e R e p. o f M o l d a v i Border crossing points a Iași Impeded-distance × 100 Euclidian distance 100–150 151–200 201–300 301–400 401–800 The influence of space roughness on the growth of impeded-distance Low High Author of contents/avtor vsebine: Tudora D., Eva M. Author of map/avtorica zemljevida: Tudora D., Eva M. Source/vir: Topographic Maps of Romania – 1:50.000, Military Topographic Department; © University »Alexandru Ioan Cuza« of Iași, 2012 Figure 3: Space roughness influence on the growth of impeded-distance. In the first stage of analysis, the nodality is calculated according to the concept of šdegree centrality’, as an expression of local centrality (Freeman 1979). The degree of centrality involves calculating the num- ber of edges connected to a given node. Given that the importance of road junctions within a region may depend on much more edges that are not necessarily related to the junction in question, the present article proposes calculating nodality by extracting the total number of junctions together in a buffer of 11,008 km, i.e. the average radius of the circles circumscribing Thiessen polygons for the 881 junctions within the region. Junctions located in areas well served by the means of communication, where many intersections occur, will be loaded with a high value of nodality, unlike peripheral junctions. Resulting values vary between 1 and 26 and will be called gross nodalities (figure 4). 4 Transscalar analysis In the second stage, junctions attach a nodal space, defined by the potential of interaction between them and the population points within the region. Nodal gravity increases directly proportional to the value of gross nodality and inversely proportional to the square of the distance separating the junctions from the population points. The area of nodal influence and the potential of interaction attached to it will be used in the formu- la for calculating the adjusted nodality. This will be estimated depending on the demographic mass attracted 107 Daniel Tudora, Mihail Eva, A geographical methodology for assessing nodality of a road network. Case study on the western Moldavia 0 60 km U k r a i n e R e p. o f M o l d a v The value of gross nodality i a 26 County and national roads The limits of the nodal polarization areas Altitude (m) 0–200 201–800 801–2,057 Author of contents/avtor vsebine: Tudora Daniel, Eva Mihail Author of map/avtorica zemljevida: Tudora Daniel, Eva Mihail Source/vir: Topographic Maps of Romania – 1:50.000, Military Topographic Department; Earth Remote Sensing Data Analysis Centre, Japan. © University »Alexandru Ioan Cuza« of Iași, 2012 Figure 4: The gross nodality and the nodal polarisation areas. by each nodal influence area and inversely proportional to the impeded-distance from the junction to the clos- est barycentre. Because there are three categories of barycentres, each junction disposes of three types of adjusted nodality: the natural adjusted nodality, the county adjusted nodality, and the regional adjusted nodality. 4.1 The natural adjusted nodality The natural adjusted nodality identifies the rapport the network maintains with the over-local spatial sys- tems, focusing on the ability of graph nodes and segments to generate infra-territorial centrality. In addition, it notices the manner in which the ideological/driven projection of the communication routes systems neglected or overlooked the importance of discrete relations, eliminating inter-nodal competition. In the condition of an ad litteram adaptation of social structures to the natural ones, artificial net- works choose the easiest routes, dictated by the particularities of substrate: roads follow river configurations, intersections overlap with natural convergence areas, such as confluences, depressions, gathering water markets, or areas of narrowing beds. Because modern society has persisted to ignore as far as possible the nature determinisms, but also from the necessity to produce reliable, fast, customized, and available connections, the initial network was supplemented by new segments as well as with re-accessibilizations of the pre-existing ones. The last were able to evolve to the stage in which nature had to readjust to the new nature: redrawing of river segments, including confluences, embankments, debit changes, or regularizations, cutting of slopes, intakes, under- grounding the courses of rivers, etc. Based on gravity laws and interaction scenarios, the adjusted nodality model at the level of natural reference systems intends to notice the force through which the space (as a physical environment) was able to imprint the social systems its own trajectories, defining inertias, regularities with permanentiza- tion trends, hard to surmount by other logics, whether more efficient. In the same manner, it may be a sign stipulating deviations, repositioning and reconfigurations of socio-spatial structures, focusing on what is atypical, residual. 108 Acta geographica Slovenica, 54-1, 2014 The classification of hydrographical basins respected the classical methodology (Gravelius 1914), the identification of watersheds being realized on the cartographic support provided by the 1 : 50,000 topo- graphic maps. Furthermore, second order basins according to Gravelius system and the largest of the third and fourth orders were divided into sub-basins, thereby achieving a relatively balanced 27 areas for which the ratio maximum area / minimum area does not exceed 1.86. Adjusted nodality was calculated for each node separately according to the following formula: P N = P b ⋅ (4) a j D 2 i where N is the adjusted nodality, P – the total population polarized by the respective junction, P – a j b the population of the polarizing barycentre, and D – the impede-distance between junction and bary - i centre. It should be noted that the calculation method allows each node to select its own barycentre, inde- pendently of the affiliation to a particular hydrographical basin, advantaging the junctions positioned on axis that transcend the hydrographical basins. 4.2 The adjusted nodality at the county level The second nodality index personalizes the same processes reported in the case of reference system centred on conventional hydrographical basins, indicating that the establishment of clear landmarks, of adminis- trative nature, requires for the reconfiguration mechanisms to become particular situations of the accretion and decoupling. As in the previous case, the discourse focuses on the problem of nodal spaces that lose the centrality of their own administrative structures, being attracted through structural or serial fragmentation process- es to higher nodality structures, created by differential accessibility and interaction. The method of calculating the relations of interaction between the nodal spaces and the county barycentres allows junctions to select their own barycentre of attractiveness. The emissivity of nodal spaces is composed of two vectors: a demographical one directly proportional to the localities size which require a specific network node and a metric one inversely proportional to the distance that separates the respective junction from the barycentres likely to come into interaction with the concerned nodal space. The highlighting of the nodal spaces not adapted to their own administrative structure on the one hand stresses the incomplete functionality of some infra-county interactions and, on the other hand, it indicates the underestimation of some distances to which big cities can impose themselves. 4.3 The adjusted nodality at the regional level We underline the increased importance of the nodality centred on the city of Roman and the reticular drainage produced by the natural convergences from the median area of the Siret axis, identifying the sub- jective role induced by the potential factor of the place in the context of selecting such a level of connectivity analysis. The demographical size acts secondarily in the final value of regional nodal index, while the imper- ceptibility originates from how each junction selects, depending on impedance and network complexity, certain preferential trajectories through which to access the centre. Such contingencies explore historical deficiencies, warning on a north-south imbalance regarding the drainage efficiency. The latest population, the resizing of the settlements network and systems of com- munication routes depending on peripheral or extra-regional urban landmarks, betrays the reticular immaturity of the counties in southern Moldavia, compared to the north. Here, the filter of Christallerian balance achieved the transition from archipelago type of territorial structures to the ones related to rapid intermediary spaces. 109 Daniel Tudora, Mihail Eva, A geographical methodology for assessing nodality of a road network. Case study on the western Moldavia 4.4 The total nodality and the reticular importance of road segments In order to obtain the total nodality, we made use of cumulative integration of adjusted nodalities for the three levels of analysis, these being found successively in the terms of amount, and being the more influential as they are hierarchical closer to the over-local system of reference: N = N + N ⋅ N + N ⋅ N ⋅ N (5) t ab ac ab ar ac ab where N is the total nodality; N – the adjusted nodality at the level of conventional hydrographical basins; t ab N – the adjusted nodality at the county level; N – the adjusted nodality at the regional level. ac ar The importance of road segments was calculated using the arithmetic mean of total nodalities related to the junctions that frame the respective segment, the roads linking important or very important cross- roads being favoured. N + N j 1 j I = 2 (6) s 2 where I is the importance of road segments, N – the total nodality for the starting junction, and N – s j1 j2 the total nodality for the ending junction (related to the opposite end of the segment). Segment level analysis appreciates with greater accuracy the dysfunctions, convergences / divergences and reticular fragilities the road network in Moldavia hides (figure 5). Firstly, the segments cumulating continuous nodality are distinguishable, thus obtaining nodal linearity and becoming segments with a trans-regional character. It is true that such linearities are rare and incomplete, the only continuous sec- tion being created by NR2, opportunities for cross coupling on the east-westward direction being interrupted or disrupted for reasons of impedance or the appearance of a network capilarization process. The East Carpathians orographic barrier blocks the coherence of reticularity marked by the high values of nodality 0 60 km The value of total nodality < 0.09 0.10–0.23 Săveni 0.24–0.45 29 0.46–0.90 2 Botoșani 0.91–1.86 29 1.87–3.36 17 3.37–8.24 17 Iași 8.25–31.12 17 2 28 28 > 31.13 15B 2 Târgu Mureș 2 The value of total nodality The importance Border crossing 2 of segments points 0.004–0.500 The main entry / exit points 2 0.501–1.00 of Moldavia 1.01–2.00 National roads 2.01–10.00 County roads 2 > 10.01 The name of the 15B National Road (DN) Author of contents/avtor vsebine: Tudora D., Eva M. Author of map/avtorica zemljevida: Tudora D., Eva M. Source/vir: Topographic Maps of Romania – 1:50.000, Military Topographic Department © University »Alexandru Ioan Cuza« of Iași, 2012 Figure 5: The importance of road segments and the total nodality. 110 Acta geographica Slovenica, 54-1, 2014 specific for the segments overlapping NR28 and NR15B. This barrier brings extra impedance, but fur- ther validating the choice correctness of the highway section Iaşi – Târgu-Mureş along this route. In the counties of Suceava and Botoşani, a similar case is represented by the consecutive nodalities created by NR17 and NR29, which, except for short segments nodally vitiated by impedance (due to the existence of moun- tain passes), maintain their reticularity up to the east of Botoşani City. Supporting a highway project along this section could solve the deficiency of regional transversality in the northern half of Moldavia. Reticular divergences identify areas in which the segments nodality decreases from a centre with high nodal value (over-local intersections) to neighbouring areas, disadvantaged by the peripheral position within the region and by the local network inconsistency. The example given by the segments nodality centred on the Săveni town is the most convincing at the regional level. The presence of segments with such a high nodality is influ- enced by the ability of the intersections from Săveni town to transfer upon some short sections (10 to 20 km) the nodal value made by an initial vertex. This sort of ribs with a rudimentary degree of centrality explain an inadequate maturity of the local networks and will have a negative effect on the subsequent data processing, with the capacity of corrupting the multivariate analysis at the nodal spaces level, because from the statistic point of view the convergence and the divergence will present confuse signs. The reticular hiatus are repre- sented by spaces with very low nodality, which interfere with areas that present high nodality, having the deficiency of blocking the fluidity within the network. Their insertion within space reflects the vulnerability of reticu- lar systems in front of the natural support roughness and compels the network to reconfiguration, which by permanentization creates inertia and behaviours specific for the anisotropic environments. 5 Applicability and relevance of the methodology The analysis results can be used further to determine vulnerabilities and inconsistencies existing in a given reticular system. For this purpose, it is necessary to calculate the average importance of road segments crossing each of the 695 nodal polarisation areas. The difference between the initial number of junctions (881) and the number of polarization nodal areas (only 695 instead of 881) is due to the fact that the junc- tions located at distances of less than 500 m from each other were merged (they were considered acting as one single junction with a higher gross nodality). Furthermore, other junctions were eliminated from the analysis in the case they do not polarize any locality. The use of the arithmetical average was preferred in the detriment of the representation of the gross values of the total nodality because of the fact that in this way one can obtain a more suggestive spatial image of the nodality at the level of polarization area by indirectly including in the formula the values of the neighbouring junctions: n ∑ I N i 1 si = = (7) ap n where N is the average nodality at the level of the nodal polarization area, I – the importance of the road ap si segment calculated using the formula (6), and n – the number of road segments which cross the nodal polarization area. The usage of nodal polarization areas has the advantage of surprising the central spaces at regional level, dictated often by the existence of several powerful urban centres nearby, generators of convergence points between county and national roads, but it has the disadvantage of insufficient iden- tification of the importance of lanes created by the main road communication ways. Despite all of these deficiencies, the mapping of the nodality at the level of nodal spaces outlines sever- al incoherencies of the reticular space of Moldavia, configured by ideological principles or by administrative attachment, being ignored the collinearities of the network at the trans-county scale or those customized within the areas of convergence generated by secondary nodalities: • The reticular fragmentations of the sub-mountainous area situated southwest of the convergence area centred on the Onești City could be attenuated by coupling the axes situated along the rivers flowing in the area, there being many possibilities for welding some routes. • The very low reticularity of northern part of Galați County claims a reconfiguration of the network depend- ing on the presence of the most important road hub of the area, Bârlad City. It also depends on the border points, trans-national transfer niches of several local nodalities, significantly important for decongest- ing rural spaces and for stimulating commercial relations specific for areas such as dead-angle, bottom of bag, or abandoned peripheries. 111 Daniel Tudora, Mihail Eva, A geographical methodology for assessing nodality of a road network. Case study on the western Moldavia Border crossing 0 60 km points U k r a i n e Siret The main points of entry / exit of R Botoşani e Moldavia Suceava p. o City population (inh.) f M 320.000 o l 80.000 Iaşi d a v County roads i Piatra Neamţ a Roman National roads The value of nodality at the level of nodal County limit polarisation areas Vaslui Very low Bacău Low Onești Bârlad Low to medium Medium Medium to high High Focşani Very high Galaţi Author of contents/avtor vsebine: Tudora Daniel, Eva Mihail Author of map/avtorica zemljevida: Tudora Daniel, Eva Mihail Source/vir: Topographic Maps of Romania – 1:50.000, Military Topographic Department © University »Alexandru Ioan Cuza« of Iași, 2012 Figure 6: The value of nodality at the communal and nodal polarisation areas level. • Consecutive coupling the county and national roads linking directly the cities of Botoşani and Iaşi may do the nodality transfer from the northern extremity of Moldavia to the main nodal point of the region, Iași, more easily. This sort of route would regard the balance created by the urban couple Suceava – Botoșani, would shorten with approximately 50 km the distance between the border crossing point of Siret and Iași Cities, providing at the same time the revitalization of some peripheral rural areas like those situated in the northern part of the Iasi County. Depending on the aims of each particular study, the insufficiencies generated by the analysis at the level of nodal spaces may be further corrected by replacing them with an administrative maillage, such as com- munal clippings. 6 Conclusion The article proposes a glossary suitable for reticular environments. Its advantage comes from the finely epistemological delimitations between closely related terms such as gross nodality, adjusted nodality, total nodality, reticular capilarization and reticularity. The conceptual limits between different terms are being established from the perspective of the methodology applicable to each of them. Furthermore, the methodology allows the conversion of concepts in quantitative benchmarks, sub- sequently benefiting from the advantage of being easily transposable into cartographic materials. Using them can be a starting point in territorial planning processes due to transversal dimension of indicators. For example, the values of total nodality provide information about the existence of nodal regions and their polarising centres, about discontinuities inserted between different homogenous structures or about the subjacent dimension of some territorial points that can constitute pivotal areas in shaping future poli- cies aimed at strengthening territorial cohesion or competitiveness. 7 Acknowledgements The research reported in this paper is funded by the Romanian National Council of Scientific Research in Higher Education (CNCSIS) as part of the research project IDEI 1987. We would also like to thank 112 Acta geographica Slovenica, 54-1, 2014 the Department of Geography of the University »Alexandru Ioan Cuza« of Iasi for the permanent sup- port during the research project and the anonymous referees for their constructive comments and useful recommendations. 8 References Banister, D. 2002: Transport planning. London. Berdica, K. 2002: An introduction to road vulnerability: what has been done, is done and should be done. Transport policy 9-2. DOI: http://dx.doi.org/10.1016/S0967-070X(02)00011-2 Berke, E. M., Shi, X. 2009: Computing travel time when the exact address is unknown: a comparison of point and polygon ZIP code approximation methods. International Journal of Health Geographics 8-1. DOI: http://dx.doi.org/10.1186/1476-072X-8-23 Black, W. R. 2003: Transportation: a geographical analysis. New York. Combes, P. P., Lafourcade, M. 2005: Transport costs: measures, determinants, and regional policy impli- cations for France. Journal of economic geography 5-3. DOI: http://dx.doi.org/10.1093/jnlecg/lbh062 Curl, A., Nelson, J. D., Anable, J. 2011: Does accessibility planning address what matters? A review of cur- rent practice and practitioner perspectives. Research in transportation business & management 2. DOI: http://dx.doi.org/10.1016/j.rtbm.2011.07.001 Debrie, J., Eliot, E., Soppe, M. 2005: Un modèle transcalaire des nodalités et polarités portuaires: exem- ple d'application au port de Hambourg. Mappemonde 79. Internet: http://mappemonde.mgm.fr/num7/ articles/art05304.html Ducruet, C. 2008: Typologie mondiale des relations ville-port. CyberGeo. Article no. 417. http://dx.doi.org/ 10.4000/cybergeo.17332 Earth remote sensing data analysis centre. Internet: http://www.gdem.aster.ersdac.or.jp/search.jsp (15. 10. 2011). Fleming, D. K., Hayuth, Y. 1994: Spatial characteristics of transportation hubs: centrality and intermediacy. Journal of transport geography 2-1. DOI: http://dx.doi.org/ 10.1016/0966-6923(94)90030-2 Freeman, L. C. 1979: Centrality in social networks: Conceptual clarification. Social networks 1-3. Gravelius, H. 1914: Flusskunde. Berlin. INS 2002: Census of population and dwellings. National institute of statistics, Bucharest, Romania. Knowles, R. D. 2006: Transport shaping space: the differential collapse of time/space. Journal of transport geography 14-6. DOI: http://dx.doi.org/10.1016/j.jtrangeo.2006.07.001 Knowles, R. D., Shaw, J., Docherty, I. 2008: Transport geographies: mobilities, flows and spaces. Malden. Matthiessen, C. W., Schwarz, A. W., Find, S. 2002: The top-level global research system, 1997–1999: Centres, networks and nodality. An analysis based on bibliometric indicators. Urban studies 39, 5–6. DOI: http://dx.doi.org/0.1080/00420980220128372 Matthiessen, C. W., Schwarz, A. W., Find, S. 2006: World cities of knowledge: research strength, networks and nodality. Journal of knowledge management 10-5. MTD 1992: Topographic maps of Romania, 1 : 50.000, Military topographic department, Ministry of national defense, Bucharest. Mérenne, E. 1995: Géographie des transports. Paris. Muntele, I., Groza, O., Țucănașu, G., Rusu, A., Tudora, D. 2010: Calitatea infrastructurii de transporturi ca premisă a diferențierii spațiilor rurale din Moldova. Iași. Rathert, D. 2003: ArcScript Linear Proprieties. Internet: http://arcscripts.esri.com/details.asp?dbid=12789 (15. 10. 2011). Rodrigue, J. P., Comtois, C., Slack, B. 2009: The geography of transport systems . New York. Salonen, M., Toivonen, T., Cohalan, J. M., Coomes, O. T. 2011: Critical distances: comparing measures of spatial accessibility in the riverine landscapes of Peruvian Amazonia . Applied geography 32-2. DOI: http://dx.doi.org/10.1016/j.apgeog.2011.06.017 Sappington, J. M., Longshore, K. M., Thompson, D. B. 2007: Quantifying landscape ruggedness for ani- mal habitat analysis: a case study using desert bighorn sheep in the Mojave Desert. Journal of wildlife management 71-5. Shaw, S. L. 2006: What about time in transportation geography? Journal of transport geography 14. DOI: http://dx.doi.org/10.1016/j.jtrangeo.2006.02.009. Taaffe, E. J., Gauthier, H. L., O'Kelly, M. E. 1996: Geography of transportation. New Jersey. 113 114 Acta geographica Slovenica, 54-1, 2014, 115–130 THE IMPORTANCE OF VULNERABLE AREAS WITH POTENTIAL TOURISM DEVELOPMENT: A CASE STUDY OF THE BOHEMIAN FOREST AND SOUTH BOHEMIA TOURISM REGIONS Josef Navrátil, Miha Lesjak, Kamil Pícha, Stanislav Martinát, Jana Navrátilová, Vivian L. White Baravalle Gilliam, Jaroslav Knotek, Tomá{ Ku~era, Roman [vec, Zuzana Balounová, Josef Rajchard ÁVOILTÁRVA NAN JA Vydra River in the Bohemian Forest in 2008. The importance of vulnerable areas with potential tourism development: a case study of the Bohemian forest and South Bohemia … The importance of vulnerable areas with potential tourism development: a case study of the Bohemian forest and South Bohemia tourism regions DOI: http://dx.doi.org/10.3986/AGS54108 UDC: 913:338.48(437.3) 502.1:338.48(437.3) COBISS: 1.01 ABSTRACT: The significance of the vulnerability of nature-rich areas with high development potential for tourism was studied using three types of data: 1) spatial distribution of tourist attractions, 2) the appeal level of these attractions, and 3) the number of visitors. The Bohemian Forest and South Bohemia were chosen as study areas. Nine types of landscape spatial appeal were identified in the study area. Two most important types were defined based on their appeal where there are rare relic features in the natural envi- ronment dominated by the presence of peat bogs and natural habitats with scrub undergrowth or virgin forests. These types were also found in the areas with the greatest potential for tourism development. However, these areas are also the most important from the point of view of nature conservation and land- scape protection in Central Europe. KEY WORDS: geography, landscape, tourism, Czech Republic ADDRESSES: Josef Navrátil, Ph. D. Department of biological disciplines, faculty of agriculture, University of South Bohemia in ^eské Budějovice Studentská 13, CZ – 370 05 ^eské Budějovice, Czech Republic E-mail: josefnavagmail.com Miha Lesjak, M. Sc. Faculty of tourism studies – Turistica, PortoroÙnivesity of Primorska, Koper, Obala 11a, SI – 6320 Portorò, Slovenia E-mail: miha.lesjakaturistica.si Kamil Pícha, Ph. D. Department of trade and tourism, faculty of economics, University of South Bohemia in ^eské Budějovice Studentská 13, CZ – 370 05 ^eské Budějovice, Czech Republic E-mail: kpichaaef.jcu.cz Stanislav Martinát, M. Sc. Department of economics, school of business administration in karviná, Silesian University in Opava, Univerzitní nám. 1934/3, CZ – 733 40 Karviná, Czech Republic E-mail: martinataopf.slu.cz Jana Navrátilová, Ph. D. Department of botany and zoology, faculty of science, Masaryk University Kotlářská 2, CZ – 611 37 Brno, Czech Republic E-mail: jananavagmail.com 116 Acta geographica Slovenica, 54-1, 2014 Vivian L. White Baravalle Gilliam Institute of technology and business in ~eské budějovice Okrùní 517/10, CZ – 370 01 ^eské Budějovice, Czech Republic E-mail: vivianamail.vstecb.cz Jaroslav Knotek, Ph. D. Department of applied and landscape ecology, faculty of agronomy, Mendel University in Brno Zemědělská 1, CZ – 613 00 Brno, Czech Republic E-mail: jarda.knotekauake.cz Tomá{ Ku~era, Ph. D. Department of ecosystem biology, faculty of science, University of South Bohemia in ^eské Budějovice Brani{ovská 31, CZ – 370 05 ^eské Budějovice, Czech Republic E-mail: kucert00aprf.jcu.cz Roman [vec, Ph. D. Institute of technology and business in ~eské budějovice Okrùní 517/10, CZ – 370 01 ^eské Budějovice, Czech Republic E-mail: svec.roman78agmail.com Zuzana Balounová, Ph. D. Department of biological disciplines, faculty of agriculture, University of South Bohemia in ^eské Budějovice Studentská 13, CZ – 370 05 ^eské Budějovice, Czech Republic E-mail: balounazf.jcu.cz Josef Rajchard, Ph. D. Department of biological disciplines, faculty of agriculture, University of South Bohemia in ^eské Budějovice Studentská 13, CZ – 370 05 ^eské Budějovice, Czech Republic E-mail: rajchardazf.jcu.cz 117 The importance of vulnerable areas with potential tourism development: a case study of the Bohemian forest and South Bohemia … 1 Introduction The opportunity to develop recreational activities is among the main motives for creating national parks (Williams 1998) and tourism remains an important justification for park creation and development today (Hall and Lew 2009). Similar to the rural environment, these spaces offer opportunities for refreshment to people living in urban spaces that lack opportunities for everyday contact with the »environment of nature« (Olwig and Olwig 1979). Rural areas became an important space of large-scale tourism in the 1950s and 1960s for this reason (Hall and Page 2006), and then (in part since the 1990s) they also became a des- tination of ecotourism activities (Weaver 2006). For instance, in the United States the National Park System is part of the country's greatest tourist attractions, appealing to both domestic and international visitors (Goeldner and Ritchie 2009). The ongoing degradation of the environment and its urbanization are further increasing the value of the pleasure periphery in tourism (Bushell et al. 2007). These kinds of environments are then increas- ingly exposed to pressures resulting from conflicts among different types of use of such areas (Jamal et al. 2002; McClanahan et al. 2009). The risk of the degrading impact of tourism increases with the rising number of visitors (Geneletti and Dawa 2009; Heydendael 2002; Marion and Leung 2001; Nepal and Nepal 2004; Vasiljevi} et al. 2011), which consequently results in people experiencing less satisfaction from the visit (Juutinen 2011). Disregarding the other influences, three interests clash at the intersection of these vul- nerable areas from the tourism point of view: nature conservation (Hall and Lew 2009), ecotourism, and large-scale tourism activities (Epler Wood 2002; Weaver 2006). According to Anderson and Brown (1984), one of the main tools for preventing conflicts is recreational displacement – that is, a way in which all three interest groups are able to achieve maximal satisfaction (Hall and Page 2006). Studies in tourism locations and the importance of these tourist attractions as location factors are the main areas of research in tourism geography (Williams 1998). This has taken place since the begin- ning of the twentieth century (Benthien 1997). The key approaches were crystallized in the late 1960s and the early 1970s (Hall and Page 2006). Studies and dissertations on these problems agree that core resources are fundamental for localization in tourism (following Ritchie and Crouch 2003), and the highest impor- tance within these core resources is attributed to undeveloped recreation resources (Chubb and Chubb 1981) of natural or cultural origin (Ritchie and Crouch 2003). The basis for visitation management in partic- ular locations of destination created by knowledge of the distribution of attractions (Kostrowicky 1970) and the extent of their importance for visitors (Linton 1968). This knowledge allows management to make decisions directed aimed at satisfying these two contradictory requirements. It is essential that these attrac- tions not be performed separately in the space, but that they create spatial systems of tourism (Lau and McKercher 2007) that are geographically recognizable (Wall 1997) as the spatial types of a recreational landscape (Burger 2000). These types provide various motives for different types of visitors (Horner and Swarbrooke 1996) and similarly show the various values of habitats for nature conservation (Ku~era 2005). Accordingly, the main aim of this article is to present testing methods for evaluating the relative impor- tance of vulnerable areas for tourism development in large areas. 2 Methodology 2.1 Study Area This article examines the South Bohemian Region (Cz. Jiho~eský kraj), an area with a temperate climate in the southern part of the Czech Republic along the border with Germany (Bavaria) and Austria (Upper Austria; Cetkovský et al. 2007; [vec et al. 2012). The selected area comprises two tourism marketing regions: South Bohemia and the Bohemian Forest (Cz. [umava, Figure 1). The territory extends throughout a rather geographically diversified part of the Czech Republic. Bohemian Forest National Park (Cz. Národní park [umava), the Třeboň Protected Landscape Area (Cz. Chráně ná krajinná oblast Tř eboň sko), the Bohemian Forest Protected Landscape Area (Cz. Chráně ná krajinná oblast [umava), and the Blanský Forest Protected Area (Cz. Chráně ná krajinná oblast Blanský les; Figure 2) are the largest conservation areas in the region studied (Navrátil et al. 2012b). 118 Acta geographica Slovenica, 54-1, 2014 20 0 20 40 km Figure 1: Topography of the study area (ArcData Praha, s. r. o.). 8 10 19 12 20 21 4 9 14 18 16 15 1 4 11 3 5 2 17 13 6 National Park 7 Protected Landscape Area 20 0 20 40 km Natural Park Figure 2: Conservation areas within the study area (1 – Bohemian Forest National Park, 2 – Blanský Forest Protected Area, 3 – Trěbonˇ Protected Landscape Area, 4 – Bohemian Forest Protected Landscape Area, 5–21 – natural parks). 119 The importance of vulnerable areas with potential tourism development: a case study of the Bohemian forest and South Bohemia … 2.2 Data Collection It was necessary to gather three types of data to accomplish the defined aim of this article: the spatial dis- tribution of tourist attractions, the appeal level of these attractions, and the number of visitors in individual territorial units of the study area. A database of potential attractions was created to identify the distribution of tourist attractions. The individual attractions were identified based on tourism geography literature (Mariot 1983; Ritchie and Crouch 2003; Hall and Page 2006; Ku{en 2010). The database only covers permanent attractions; that is, those that cannot be moved or quickly rebuilt based on tourist demand (Gunn 1997). Primarily, this involves components of appearance, culture, and history (Ritchie and Crouch 2003). Sixty-nine attraction types were localized: those found statistically important for further calculations are shown in Table 1 (for the entire list, see Navrátil et al. 2013a). The appeal of the destinations was investigated for partial segments of demand. They were identified by surveying visitors at important sights and areas within the study area and model segments. Visitors to the study area were surveyed on roughly sixty attractions in the study area from 2009 to 2011. A database of 3,776 completed questionnaires was developed. In addition, an experiment was carried out on three model segments of tourists on the eco-tourism/mass-tourism continuum. Students were utilized for this research (Palmer and Hofmann 2001). We chose university students as model segments: • business students representing »large-scale tourists,« • ecology students representing »eco-tourists,« and • agriculture students representing »neutral tourists«; (these methods are based on Navrátil et al. 2013b). The students filled out 396 questionnaires (the questionnaire return rate was 61%). The intensity of recreational activities during leisure activities away from a permanent residence was used as the basic ele- ment of segment identification: the questioning tool used is described in detail in Navrátil et al. (2010). The questionnaire was filled out by students representing particular model types of visitors. The students were also asked to complete a questionnaire seeking to identify the amount of appeal of the individual attrac- tions. Q-sort methodology was used (Doody et al. 2009). A setup of eleven columns was used (Barry and Proops 1999; Steelman and Maguire 1999). The respondents were asked to sort the photographs of the attrac- tions according to their perception of interest as a place to visit. In this Q-sort study, +5 indicates »This has crucial importance for me while choosing a destination« and –5 indicates »This has no importance for me while choosing a destination.« The number of attractions for the individual columns was con- structed as close as possible to a normal distribution (1-2-4-7-12-17-12-7-4-2-1). The numbers of visitors in the partial territorial units of the study area were taken from our previ- ous research (Navrátil et al. 2012a). The methodology is described in detail in Navrátil et al. (2012a, 52 and 53). The GIS shapefile was used for the subsequent calculations in this article, which provided data on the total visitor frequency model of partial territorial units in a regular hexagonal net according to input data for 2010. 2.3 Data Processing and Analysis The appeal of the area was evaluated in the identical artificial spatial units as the visitor frequency model of the study area: a regular hexagonal network with hexagons approximately 3 km2 (Navrátil et al. 2012a). The presence of an attraction (in the case of a point shapefile) was ascertained in each hexagon. Polygonal and linear shapes had to be converted to points first. Lines and polygons were cut by the shape of the hexag- onal artificial spatial units and then centroids of the new polygons and lines were calculated. Then the presence of these points in hexagons was ascertained. The typology of the partial territorial units was based on a combination of the presence of the indi- vidual attraction types in each hexagonal artificial spatial unit. The TWINSPAN hierarchical divisive method (Hill 1979) was used. The division in TWINSPAN is made according to the results of the correspondence analysis on the first axis. This is processed by the settings of the »cut level« analytical operation that was chosen for levels 0%, 5%, and 25% in the representation of the attractions. This division was made in four degrees. The attractions with the highest fidelity were used (i.e., the highest fidelity to the group); those with a φ-coefficient value (Tichý 2002) greater than 10 were used to describe the newly created groups. 120 Acta geographica Slovenica, 54-1, 2014 Table 1: φ-coefficient values of core resources for spatial attraction types (only resources with a φ-coefficient greater than 10 for at least one type of area are shown). 1. 2. 3. 4. 5. 6. 7. 8. 9. Important Wooded Abandoned Upland Wild Mountain Rural Urban Pond non-forest rocky border plains river foothills areas areas areas habitats slopes areas valleys Number of territories 161 226 226 144 210 951 2055 710 218 Peat bog 63.2 10 – – – – – – – Virgin or near-virgin forest 5.1 57.2 – – – – – – – Rocks and crags 9.5 40.5 – – – – – – – Mountain landscape 0.2 13 1.7 – 3.3 – – – – Pre-WWII fortification – 10.3 3.7 – 2 – – – – Dilapidated village 9 3.7 45.6 – – – – – – Spring with drinking water – 7.2 26.6 – – – – – – Groomed ski hill or slope – 8.8 12.9 2.5 – – – – Carved valley landscape – – – – 80.7 – – – – Climbing opportunity – 6.7 – – 20 – – – – Cave – 1 – – 11.4 0.8 0.3 0.8 – Tower house – – – – 10.8 – – 3.9 – Ruins of tower house – 1.2 – – 10.2 – – 1.7 – or other monument Predominantly agricultural – – – – – – – 52.6 – landscape Church – – – – 1.4 – – 35.7 – Historical town building – – – – 0.9 – – 25.9 1.9 Castle – – – – 3.1 – 1.2 20.3 – Tennis court – – – – 1.9 – – 16.4 3.7 Remnants of fortresses or fortified settlement – – – – – 0.3 4.8 15.1 1.1 Town monument reservation – – – – 4.8 – – 11.7 4.5 Jewish cultural monument – – – – 9.9 – – 11 – Calvary chapel – – – – 8.9 – 5.9 10.9 – Broad flood-meadow landscape – – – – – – – 5 45.5 Dam (pond, water barrier, artificial channel) – – – – – – – 2.6 13.1 Monuments of popular – – – – 3.3 0.9 2.8 0.5 10.4 architecture Rare plant 59 23.4 – – – – – – 8.6 Rare animal 54.2 17.1 – – – – – – 9 High-elevation plateau landscape 16.5 3.7 4.2 31.6 – – – – – Flatland landscape 13.7 – – – – – – – 67.5 Cirque landscape – 10.8 – 13.9 – – – – – Recreational fishing – – – – 57.8 – 0.1 1.5 13.2 Boating – – – – 41.1 – – – 21.1 Water-powered mill or iron mill – – – – 10.3 – 0.1 10.5 0.1 Pond landscape – – – – – – 16.6 – 59.8 Town landscape – – – – – – – 20.5 27.3 Meadow vegetation near 18.6 18 – – – – – – 13.2 traditional farming Hillsides and rocky mountain – 35.3 38.2 33.6 – 2.5 – – – ridge landscape Observation and viewpoint – 10.9 16.3 7.3 – – – 11.9 – Highland landscape – – 1.8 – 23.5 20.9 25.9 24.8 – Forested landscape – – 3.6 – 20.7 14.7 22.5 13.8 – Mixed forest, meadow, 11.8 21.2 23.2 26.2 3.8 13.7 – – – and field landscape 121 The importance of vulnerable areas with potential tourism development: a case study of the Bohemian forest and South Bohemia … The demand segments were identified by cluster analysis (Ward Method, Euclidean distance) of the ques- tionnaires from both surveys (the scale of the rate of participation on partial recreational activities). The estimated credibility loss ratio was 50% as in Real et al. (2000). The questionnaires from the model segments (i.e., students) were selected from the identified clusters. The average appeal value for the par- ticular attractions for each demand segment was calculated. The means were converted into positive values (the results of the Q-sort experiment varied between –5 to +5) and then transformed by power because the data were obtained from the Q-sort study. The final appeal value of each attraction type for the demand segment was relatively expressed as a share of the appeal of the partial attraction type in the maximum appeal value achieved by the most attractive attraction type. These values were assigned to a particular attraction type included in the GIS database, individually for each demand segments. The appeal of the particular types of territory was determined as a sum of the appeal of all of the attrac- tions located in each hexagon for the partial demand segments. The differences in the average appeal among the types of areas were investigated by one-way ANOVA with Tukey unequal N HSD post-hoc tests (Quinn and Keough 2002). Subsequently, the development potential of the types of areas was assessed. First it was necessary to standardize the data on the appeal rate and data from the visitor frequency model to make the calculation possible. The development potential was evaluated as the simple difference between the standardized appeal values and standardized values of visitor frequency model in each hexagonal artificial spatial unit. The dif- ferences in the average development potential (among the types of areas) were investigated using one-way ANOVA with Tukey unequal N HSD post-hoc tests. The adjustments of the spatial data were carried out using Quantum GIS software (Athan et al. 2011). STATISTICA 10.0 software (StatSoft 2011) was employed for the cluster analysis calculations and one-way ANOVA. Calculation of TWINSPAN was done using JUICE software (Tichý 2002). 3 Results and discussion Nine spatial attraction types were identified in the study area. A comparison of the values of φ-coefficients of the attractions of the partial types (Table 1) and spatial distribution of these types (Figure 3) makes it possible to confirm the validity of the database that was developed. The first type, called »important non-for- est habitats« (Figure 4), is typical by appeal given by the presence of important (protected) species of plants and animals associated with peat bogs and meadows. High-elevation plateaus prevail in these types of land- scapes. This type can especially be found in the high elevations of the Bohemian Forest. However, they can also be found in low-basin areas in the Třeboň Protected Landscape Area, whose peat bogs are of global importance and are protected within the Ramsar Convention on Wetlands as the Třeboň peatlands and Třeboň fishponds (Chytil and Hakrová 2001). The second type of appeal is also indicated solely by the natural place of interest. In this case, the sites are linked to wooded slopes with rocks and landscapes with hillsides and rocky mountain ridges. Therefore it was named »wooded rocky slopes« (Figure 5). It is found in the highest parts of the Bohemian Forest and the highest parts of the Nové Hrady Mountains park. The third type is spatially complementary to the previous ones. It is called »abandoned border areas« (Figure 6) because the abandoned and ruined villages originated with the expulsion of Germans from Czechoslovakia and the subsequent establishment of the Iron Curtain after the Second World War. Springs in these villages are typical for this type. These areas offer various opportunities to develop tourism; larg- er non-wooded areas can be found; these offer panoramic views and make it possible for tourism providers to build downhill ski areas. In addition to the Bohemian Forest and the Nové Hrady Mountains, this type can also be found in the Nová Bystřice Uplands (Cz. Novobystř ická vrchovina). The fourth type can be described as »upland plains« (Figure 7) because it is almost exclusively con- nected to high plateau areas in Bohemian Forest National Park and its appeal is especially due to its flat relief and adjacent forested cirque and slope areas. The plains themselves represent a unique type of land- scape and are the largest Central European remnant from the Paleogene Period up to the Tertiary, with the paleo-relief character of the peneplain (Demek and Mackov~in 2006). The appeal of the fifth type is determined by deep valleys with opportunities for fishing and boating. Pseudo-karst caves, scenic overlooks, tower houses, water-powered mills, iron mills, and opportunities 122 Acta geographica Slovenica, 54-1, 2014 N 20 0 20 40 km 1. Scientifical y important non-forest habitats 4. Upland plains 7. Rural areas 2. Wooded rocky slopes 5. Wild river valleys 8. Urban areas 3. Abandoned border areas 6. Mountain foothil s 9. Pond areas Figure 3: Appeal types in the Bohemian Forest and South Bohemia tourism regions; TWINSPAN results are displayed. for rock climbing are linked to these valleys. This type has been named »wild river valleys« and can be found in the upper course and springs of the Otava River, along the Vltava River from Vy{{í Brod to Bor{ov and from Zvíkov to Orlík, and on the Luìce River from Tábor to its confluence with the Vltava River. The sixth type is formed by hilly Hercynian relief with a mix of forests, meadows, and arable land. It is named »mountain foothills« and it covers the lower elevations of the Bohemian Forest, the Nové Hrady Mountains and its foothills, and some other areas. The seventh type covers the largest parts of the study area and its typical attractions are not signifi- cantly different from the previous type. However, the pond landscapes and landscapes without forests are more important for this type of landscape (Havlicek et al. 2012), and so it was named »rural areas« (Kone~ný 2014). Some areas were separated from the seventh type and they create an eighth type with a very typical presence of urban and exclusively agricultural landscapes with both urban and rural settlements that are important from a cultural and historical point of view. This type is completed by the presence of cultur- al and historical core tourism sites (Ritchie and Crouch 2003) such as churches, castles, and places of Jewish history. This type is called »urban areas«. The last type is determined by a flat landscape with ponds and the presence of historical urban and rural settlements, as well as important water features that are suitable for boating and fishing. This type is almost solely located in the central part of the Třeboň Protected Landscape Area and is named »pond areas«. From the nine landscape appeal types identified in the study area, two types were selected whose appeal base is the presence of rare natural features dominated by peat bogs and natural habitats with scrub under- growth or natural forests. In addition, many vulnerable ecosystems are linked to these types of plains, wild mountain river valleys, and vertically based ecosystems (Chytrý 2012). 123 The importance of vulnerable areas with potential tourism development: a case study of the Bohemian forest and South Bohemia … ÁV IL O T IL Á T R Á V R A VA NF N E A S N JO JA Figure 4: Important non-forest habitats: the Moss Peat Bog (Cz. Rokytecká slat’ ), the Bohemian Forest (left) and wooded rocky slopes of the Giant's Castle Mountain (Cz. Obrˇí hrad), the Bohemian Forest. The individual types were primarily defined based on appearance (Ritchie and Crouch 2003). This is due to the natural combination of attraction types based on the natural environment (Hall and Lew 2006) and the opportunities for human use (Crang 1998). Nevertheless, a type dependent on cultural and his- torical attractions was also found (McKercher and du Cros 2008). The total appeal for each hexagonal artificial spatial unit was then calculated. The most significantly attractive areas are those in the first and the second types, which cover important non-forest habitats and wooded rocky slopes (Figure 8). The following types have a medium appeal rate: wild river valleys, urban areas, abandoned border areas, and pond areas. A low appeal rate was calculated for rural areas, moun- tain foothills, and upland plains. The comparison of the appeal in each hexagonal artificial spatial unit with the visitor frequency model makes it possible to identify areas where a relative surplus of appeal (with respect to visitors) is evident. There are two such area types: important non-forest habitats and wooded rocky slopes (Figure 9). A mod- erate appeal surplus was also detected in urban areas as well as in rural areas. However, visitor frequency is high in upland plains and pond areas (and less so for other types). Thus highly vulnerable areas are most important, where potentially increasing visitor numbers could impact other aspects of these areas (Pickering 2010), especially nature and landscape conservation (Bushell et al. 2007). Thus, using these areas for tourism activities is very problematic and undesirable because of continued degradation of the natural environment (Boucníková and Ku~era 2005; Guth and Ku~era 2005). 4 Conclusion From the point of view of territory type, this model has identified naturally important non-forest habi- tats and wooded rock slopes as being the most attractive for tourism development. They are highly visited and they also have high further development potential. These areas are also among the most important ones from the point of view of nature and landscape protection in Central Europe (Chytrý 2012). This aspect of the research corresponds to reality because conflicts regarding different utilization of this study 124 Acta geographica Slovenica, 54-1, 2014 ÁVOILTÁRVA NAN JA Figure 6: Abandoned border areas: the village of Pohorˇí na [umaveˇ, the Nové Hrady Mountains. ÁVOILTÁRVA NAN JA Figure 7: Upland plains: the Gerl Glassworks (Cz. Gerlova Hut’ ), the Bohemian Forest. 125 The importance of vulnerable areas with potential tourism development: a case study of the Bohemian forest and South Bohemia … 2,8 f 2,6 f 2,4 2,2 e 2,0 d 1,8 cd bcd Appeal value 1,6 ab abc 1,4 a 1,2 1,0 0,8 1 2 3 4 5 6 7 8 9 Attraction types Figure 8: Appeal of individual attraction types (the numbers on the x axis correspond to the landscape types in Figure 3 and Appendix 1). The averages and 95% intervals of reliability are displayed. Result of one-way ANOVA ( F = 108.95; d. f. = 8; p < 0.001). The averages marked by the same letter do not differ significantly (HSD Tukey post-hoc test for non-equal number of n, p > 0.05, n = 4,901). 0,015 e 0,010 e 0,005 d cd bcd 0,000 abc ab ent potential a –0,005 evelopm f D –0,010 –0,015 –0,020 1 2 3 4 5 6 7 8 9 Attraction types Figure 9: Identification of tourism development areas by attraction type (the numbers on the x axis correspond to landscape types in Figure 3 and Appendix 1). The averages and 95% intervals of reliability are displayed. Result of one-way ANOVA ( F = 47.15; d. f. = 8; p < 0.001). The averages marked by the same letter do not significantly differ (HSD Tukey post-hoc test for non-equal number of n, p > 0.05, n = 4,901). 126 Acta geographica Slovenica, 54-1, 2014 area have become an important political issue. It is especially a topic associated with the Bohemian Forest National Park Administration, which is the largest of this kind in the Czech Republic. With respect to the importance of the Bohemian Forest Tourist Region from the tourism and nature/landscape conser- vation points of view (cf. Prach 2010), these protected natural sites are constantly exposed to the pressure of seeking open free access (see Novinky 2010). Under such pressure along with the development drive of tourism (Hall and Page 2006), such areas are currently unable to cope with this stress (Holden 2008; Plesník 2010). With future increases in large-scale recreational tourism, the pressure of both tourists and tourism infrastructure will probably grow (Novinky 2011). Other regions in the Czech Republic, such as the Beskid Mountains with the Beskid Landscape Protected Area (Cz. Chráně ná krajinná oblast Beskydy; Havrlant 2001), the Jeseník Mountains with the Jeseník Landscape Protected Area (Cz. Chráně ná krajin- ná oblast Jeseníky; Havrlant 2010), or the Dyje Valley National Park (Cz. Národní park Podyjí; Foret and Klusá~ek 2011) have experienced a similar situation as well. The methodological approach presented is based on a combination of different approaches for eval- uating the appeal of the core sources of tourism (Ritchie and Crouch 2003), whose core lies not in typological- spatial analysis, contrary to the bulk of similar studies based on the cultural environment (e.g., Topole 2009; Vuji~i} et al. 2011), but in analysis of the relations of visitors to these areas. These analyses are not excep- tional in Central Europe, of course (e.g., Polajnar 2008; Pompurová 2011); nevertheless they are not usually directly linked to concrete spatial elements and are usually related to the selection of tourism products or are the result of expert assessments (Bína 2002). The examples of the Bohemian Forest and South Bohemia tourism regions have proved that it is necessary and appropriate to employ the combined approach to evaluate of the importance of elements of natural and cultural-historical systems for the next stage of tourism development. 5 Acknowledgements The authors express their gratitude to the nineteen students that acted as data collection assistants and all those that participated in the questionnaires. The authors would also like to thank Karel Kirchner and two anonymous reviewers for their remarks on early versions of this article. This article was written with support from the Czech Science Foundation: GACR P404/12/0334 »Factors of visitors' relation to the ambi- ence of attractions in vulnerable areas.« 6 References Anderson, D. H., Brow, P. J. 1984: The displacement process in recreation. Journal of leisure research 16-1. Athan, T., Blazek, R., Contreras, G., Dassau, O., Dobias, M., Ersts, P., et al. 2011: Quantum GIS user guide, Version 1.7.0 »Wroclaw.« Internet: http://download.osgeo.org/qgis/doc/manual/qgis-1.7.0_user_ guide_en.pdf (20. 10. 2011). Barry, J., Proops, J. 1999: Seeking sustainability discourses with Q methodology. Ecological economics 28-3. DOI: http://dx.doi.org/10.1016/S0921-8009(98)00053-6 Benthien, B. 1997: Geographie der Erholung und des Tourismus. Erfurt. Bína, J. 2002: Hodnocení potenciálu cestovního ruchu v obcích ^eské republiky. Urbanismus a územní rozvoj 5-1. Boucníková, E., Ku~era, T. 2005: How natural and cultural aspects influence land cover changes in the Czech Republic? Ekológia 24-1. Bushell, R., Staiff, R., Eagles, P. F. J. 2007: Tourism and protected areas: Benefits beyond boundaries. Tourism and protected areas: benefits beyond boundaries. Waterloo. Cetkovský, S., Klusá~ek, P., Martinnát, S., Zapletalová, J. 2007: Some aspects of cross-border cooperation in Euroregions of the Czech Republic: An example of the [umava Region. Moravian geographical reports 15-1. Christofakis, M. 2010: Strategic options for tourism impacts on local sustainability: A conceptual approach. Local economy 25-7. DOI: http://dx.doi.org/10.1080/02690942.2010.532357 Chubb, M., Chubb, H. 1981: One third of our time? An introduction to recreation behaviour and resources. New York. 127 The importance of vulnerable areas with potential tourism development: a case study of the Bohemian forest and South Bohemia … Chytil, J., Hakrová, P. (eds.) 2001: Wetlands of the Czech Republic – The list of wetland sites of the Czech Republic. Mikulov. Chytrý, M. 2012: Vegetation of the Czech Republic: diversity, ecology, history and dynamics. Preslia 84-3. Crang, M. 1998: Cultural geography. London. Demek, J., Mackov~in, P. 2006: Zeměpisný lexikon ^R. Hory a níìny. Praha. Doody, D., Kearney, P., Barry, J., Moles, R., O'Regan, B. 2009: Evaluation of the Q-method as a method of public participation in the selection of sustainable development indicators. Ecological indicators 9-6. DOI: http://dx.doi.org/10.1016/j.ecolind.2008.12.011 Foret, M., Klusá~ek, P. 2011: The importance of the partnership and cooperation in the regional devel- opment exampled on Znojmo region. Acta universitatis agriculturae et silviculturae Mendelianae Brunensis 59-4. DOI: http://dx.doi.org/10.2478/s11532-011-0045-3 Geneletti, D., Dawa, D. 2009: Environmental impact assessment of mountain tourism in developing regions: A study in Ladakh, Indian Himalaya. Environmental impact assessment review 29-4. DOI: http://dx.doi.org/10.1016/j.eiar.2009.01.003 Goeldner, C. R., Ritchie, J. R. B. 2009: Tourism: Principles, practices, philosophies. Hoboken. Gunn, C. A. 1997: Vacationscape: Developing tourist areas. London. Guth, J., Ku~era, T. 2005: Natura 2000 habitat mapping in the Czech Republic: Methods and general results. Ekológia 24-1. Hall, C. M., Lew, A. A. 2009: Understanding and managing tourism impacts: an integrated approach. London. Hall, C. M., Page, S. J. 2006: The geography of tourism and recreation. Environment, place and space. London. Havlicek, M., Krejcikova, B., Chrudina, Z., Svoboda, J. 2012: Long-term land use development and changes in streams of the Kyjovka, Svratka and Velicka river basins (Czech Republic). Moravian geographical reports 20-1. Havrlant, J. 2001: The Beskydy Mountains – specific features and problems of the tourist area. Geografski obzornik 48-2. Havrlant, J. 2010: The recreational potential of the Jeseníky Region (Czech Republic and the influence of soft factors on its development). Moravian geographical reports 18-1. Heydendael, A. 2002: Sustainable tourism within the context of the ecosystem approach. Tourism, bio- diversity and information. Amsterdam. Hill, M. O. 1979: TWINSPAN – A FORTRAN program for arranging multivariate data in an ordered two-way table by classification of the individuals and attributes. Ithaca. Holden, A. 2008: Environment and Tourism. London. Horner, S., Swarbrooke, J., 1996: Marketing tourism, hospitality and leisure in Europe. London. Jamal, T. B., Stein, S. M., Harper, T. L., 2002: Beyond labels – pragmatic planning in multistakeholder tourism-environmental conflicts. Journal of planning education and research 22-2. DOI: http:/ dx.doi.org/ 10.1177/0739456X02238445 Juutinen, A., Mitani, Y., Mantymaa, E., Mäntymaa, E., Shoji, Y., Siikamäki, P., Svento, R. 2011: Combining ecological and recreational aspects in national park management: A choice experiment application. Ecological economics 70-6. DOI: http://dx.doi.org/10.1016/j.ecolecon.2011.02.006 Knox, P. L., Marston, S. A. 2001: Places and regions in global context: human geography. New Yersey. Kone~ný, O. 2014: Geographical perspectives on agritourism in the Czech Republic. Moravian Geographical Reports 22-1. DOI: 10.2478/mgr-2014-0002 Kostrowicki, A. S. 1970: Zastosowanie metod geobotanicznych w ocenie przydatności terenu dla potrzeb rekreacji i wypoczynku. Przegląd geograficzny, 42-4 Ku~era, T. 2005: Red book on habitats of the Czech Republic. Internet: http://www.biomonitoring.cz/ biotop_cerv_kn/texty/8/index.html> (24. 4. 2013). Ku{en, E. 2010: A system of tourism attractions. Tourism – an international interdisciplinary journal 58-4. Lau, G., McKercher, B. 2006: Understanding tourist movement patterns in a destination: A GIS approach. Tourism and hospitality research 7-1. DOI: http://dx.doi.org/10.1057/palgrave.thr.6050027 Marion, J. L., Leung, Y. 2001: Trail resource impact and an examination of alternative assessment tech- niques. Journal of park and recreation administration 19-3. Mariot, P. 1983: Geografia cestovného ruchu. Bratislava. 128 Acta geographica Slovenica, 54-1, 2014 McClanahan, T. R., Cinner, J., Kamukuru, A. T., Abunge, C., Ndagala, J., 2008: Management preferences, perceived benefits and conflicts among resource users and managers in the Mafia Island Marine Park, Tanzania. Environmental conservation 35-4. DOI: http://dx.doi.org/10.1017/S0376892908005250 McKercher, R., du Cros, H. 2008: Cultural tourism: partnership between tourism and cultural heritage. London. Navrátil, J., Pícha, K., Hřebcová, J. 2010: The importance of historical monuments for domestic tourists: The case of south-western Bohemia (Czech Republic). Moravian Geographical Reports 18-1. Navrátil, J., [vec, R., Pícha, K., Doleàlová, H. 2012a: The location of tourist accommodation facilities: A case study of the [umava Mts. and South Bohemia tourist regions (Czech Republic). Moravian Geographical Reports 20-3. Navrátil, J., Pícha, K., Martinát, S. 2012b: Spatial differentiation of the nature trails in the large-area pro- tected natural territories. Acta universitatis Palackianae Olomucensis facultas rerum naturalium geographica 43-2. Navrátil, J., Pícha, K., Martinát, S., Knotek, J., Ku~era, T., Balounová, Z., White Baravalle Gilliam, V. L., [vec, R., Rajchard, J. 2013a: The model of identification of the tourism development areas: A case study of the [umava Mts. and South Bohemia Tourist Regions (Czech Republic). Moravian geographical reports 21-1. DOI: http://dx.doi.org/10.2478/mgr-2013-0003 Navrátil, J., Pícha, K., Knotek, J., Ku~era, T., Navrátilová, J., Rajchard, J., White Baravalle Gilliam, V. L. 2013b: The comparison of attractiveness of tourist sites for ecotourism and mass tourism: The case of waters in mountainous protected areas. Tourismos: An international multidisciplinary journal of tourism 8-1. Nepal, S. K., Nepal, S. A. 2004: Visitor impacts on trails in the Sagarmatha (Mt. Everest) National Park, Nepal. AMBIO: A journal of the human environment 33-6. DOI: http://dx.doi.org/10.1579/ 0044-7447-33.6.334 Novinky 2010: [umava se má opět otevřít turistům, rozhodl soud. Internet: http://www.novinky.cz/domaci/ 219798-sumava-se-ma-opet-otevrit-turistum-rozhodl-soud.html (5. 12. 2011). Novinky 2011: První zónu parku [umava protne lanovka, schválili jiho~e{tí radní. Internet: http:/ www.novinky.cz/ domaci/243339-prvni-zonu-parku-sumava-protne-lanovka-schvalili-jihocesti-radni.html (5. 12. 2011). Olwig, K., Olwig, K. 1979: Underdevelopment and the development of »natural« parks ideology. Antipode 11-2. Palmer, J. F., Hoffman, R. E. Rating reliability and representation validity in scenic landscape assessments. Landscape and urban planning 54-1. DOI: http://dx.doi.org/10.1016/S0169-2046(01)00133-5 Pickering, C.M. 2010: Ten factors that affect the severity of environmental impacts of visitors in protected areas. AMBIO: A journal of the human environment 39-1. DOI: http://dx.doi.org/10.1007/s13280-009-0007-6 Plesník, P. 2010: Vplyv cestovného ruchu na biosféru. Acta geographica universitatis Comenianae 54-1. Polajnar, K. 2008: Public awareness of wetlands and their conservation. Acta geographica Slovenica 48-1. DOI: http://dx.doi.org/10.3986/AGS48105 Pompurová, K. 2011: Atraktívnosť Slovenska pre vybraný segment náv{těvníkov. E+M Ekonomie a Management 14-2.ň Prach, K. 2010: Divo~ina v ~eské krajině. Vesmír 89-12. Quinn, G. P., Keough, M. J. 2002: Experimental design and data analysis for biologists. Cambridge. Real, E., Arce, C., Sabucedo, J. M. (2000). Classification of landscapes using quantitative and categorical data, and prediction of their scenic beauty in north-western Spain. Journal of environmental psy- chology 20-4. DOI: http://dx.doi.org/10.1006/jevp.1999.0129 Ritchie, J. R. B., Crouch, G. I. 2003: The competitive destination: A sustainable tourism perspective. Wallingford. Robinson, G. M. 1998: Methods and techniques in human geography. London. StatSoft 2011: Electronic statistics textbook. StatSoft, Tulsa. Internet: http://www.statsoft.com/textbook/ (12. 10. 2011). Steelman, T. A., Maguire, L. A. 1999: Understanding participant perspectives: Q-methodology in national forest management. Journal of policy analysis and management 18-3. [vec, R., Navrátil, J., Pícha, K., & White Baravalle Gilliam, V. L. 2012: The perception of the quality of accom- modation establishments' product. DETUROPE 4-2. Tichý, L. 2002: JUICE, software for vegetation classification. Journal of vegetation science 13-3. DOI: http://dx.doi.org/10.1111/j.1654-1103.2002.tb02069.x 129 The importance of vulnerable areas with potential tourism development: a case study of the Bohemian forest and South Bohemia … Topole, M. 2009: Potential for tourism in the demographically threatened region of Jurklo{ter. Acta geo- graphica Slovenica 49-1. DOI: http://dx.doi.org/10.3986/AGS49104 Vasiljevi}, D. A., Markovi}, S. B., Hose, T. A., Smalley, I., O'Hara-Dhand, K., Basarin, B., Luki}, T., Vuji~i}, M. D. 2011: Loess towards (geo) tourism – proposed application on loess in Vojvodina region (north Serbia). Acta geographica Slovenica 51-2. DOI: http://dx.doi.org/10.3986/AGS51305 Vuji~i}, M. D., Vasiljevi}, D. A., Markovi}, S. B., Hose, T. A., Luki}, T., Hadì}, O., Jani}evi} S. 2011: Preliminary geosite assessment model (GAM) and its application on Fru{ka gora mountain, potential geotourism destination of Serbia. Acta geographica Slovenica 51-2. DOI: http://dx.doi.org/10.3986/AGS51303 Wall, G. 1997: Tourism attractions: points, lines, and areas. Annals of tourism research 24-1. DOI: http://dx.doi.org/10.1016/S0160-7383(96)00039-4 Weaver, D. 2006: Sustainable tourism. London. Weidenfeld, A., Butler, R. W., Williams, A. M. 2010: Clustering and compatibility between tourism attrac- tions. International journal of tourism research 12-1. DOI: http://dx.doi.org/10.1002/jtr.732 Williams, S. 1998: Tourism geography. London. Wood, E. M. 2002: Ecotourism: Principles, practices and policies for sustainability. Paris. 130 Acta geographica Slovenica, 54-1, 2014, 131–140 LOCALIZATION FACTORS AND DEVELOPMENT STRATEGIES FOR PRODUCER SERVICES: A CASE STUDY OF BELGRADE, SERBIA Vera Gligorijevi}, Mirjana Devedì}, Ivan Ratkaj JAKTA RNAIV New image of New Belgrade. Vera Gligorijevi}, Mirjana Devedì}, Ivan Ratkaj, Localization factors and development strategies for producer services: a case study … Localization factors and development strategies for producer services: a case study of Belgrade, Serbia DOI: http://dx.doi.org/10.3986/AGS54109 UDC: 911.375:336(497.11Beograd) 711.552(497.11Beograd) COBISS: 1.01 ABSTRACT: This article highlights the patterns of Advanced Producer Services (APS) in Belgrade and relates them to contemporary spatial and economic intrametropolitan transformations. The locational strategies of APS have influenced the creation of another center called New Belgrade next to the traditional central business district (CBD). Over the last ten years, government planning documents and the location preferences of foreign firms have made New Belgrade the most attractive business location in Serbia. In a sample of the leading APS firms in Belgrade, 129 firms are analyzed in terms of firm sector, ownership, and location. The results confirm the multipolar-monocentric pattern, which appears to be a common feature in many European cities. KEY WORDS: advanced producer services, location strategy, polycentrism, world city networks, Belgrade, Serbia The article was submitted for publication on February 23, 2013. ADDRESSES: Vera Gligorijevi}, Ph. D. Faculty of Geography, University of Belgrade Studentski trg 3/3, 11000, Belgrade, Serbia E-mail: vera.gligorijevicagmail.com Mirjana Devedì}, Ph. D. Faculty of Geography, University of Belgrade Studentski trg 3/3, 11000, Belgrade, Serbia E-mail: mdevedzicagmail.com Ivan Ratkaj, Ph. D. Faculty of Geography, University of Belgrade Studentski trg 3/3, 11000, Belgrade, Serbia E-mail: ivanratkajasbb.rs 132 Acta geographica Slovenica, 54-1, 2014 1 Introduction Advanced Producer Services (APS) are the key agents of cities and the economy (Stein 2002; Basens et al. 2010; Taylor et al. 2009; Lundquist, Oland and Henning 2008) as well as a standard unit of measurement for inclusion in the global network in the context of theories on global cities (Sassen 1991; Castells 1996; Taylor 2004). The increase in the significance of cities as centers of economic flows raises the question of whether it is possible for cities located in less-developed countries, such as Belgrade, to take a much high- er position in the world city hierarchy compared to the countries they are located in. Here it is important to note Sassen's (2001) observation that the position on the world city scale depends on the economy, which is not necessarily national, which makes these cities independent of the national economic policy. This is where the opportunity for cities like Belgrade can be seen, because in the global cities theory cap- itals of post-communist countries are considered to be the most important actors in integrating national territories into global flows (Musil 1993). Concerning APS and urban organization and structure, Hall (2001, 2004) states that today the tra- ditional CBD is of greatest importance to the location of banks and financial institutions. However, it is also being supplemented by secondary business districts and other nodes. According to Hall (2001), pre- viously established businesses remain inside the CBD, which is not the case with new companies. As the literature suggests, the internal spatial structure changes in two ways: the creation of polycentric metropolitan urban forms (Taylor, Evans and Pain 2006; Hall and Pain 2006) or development of a multi- polar-monocentric urban structure (Bourdeau-Lepage and Huriot 2005; Halbert 2004). In most European cities, the last thirty years have witnessed the rise and frequently the externalization of high-order activi- ties (producer services, financial services, headquarters of large firms) devoted to economic design, decision, and control, or more generally to economic coordination (Bourdeau-Lepage and Huriot 2005). Geographical research on producer services has focused on three issues: regional location patterns, exportability of services, and the intrametropolitan location of service activities (Coffey 1995). For the UK, Daniels (1995) found some intra-regional redistribution from large cities to adjacent towns, but the interregional pattern of producer services in Britain continues to be dominated by the southeast. Apart from deconcentration, a trend of increasing interregional and interurban specialization of APS can be observed. Examples of this are financial services in London, services auxiliary to a »control economy« in Paris, textile-engineering consulting in Lille-Roubaix-Tourcoing, services related to high-tech firms in Rhône-Alpes and southern France, engineering and software in Munich, accounting and consulting in Frankfurt, advertising in Hamburg and Düsseldorf, certification of ships in Oslo, environmental services in Copenhagen, »specialized« production areas in Portugal, and specialized engineering and management consulting in a variety of northern Italian cities and cities in Emilia Romagna (Mouleart and Todtling 1995). The multipolar urban location pattern partly has to do with the appearance of new actors such as inter- national firms, developers, and institutional investors promoting new tertiary centers, and partly with a decline in the attractiveness of central city locations. The Paris region (Île-de-France) shows an inter- nal multipolarity and a displacement of part of the economic power towards the periphery (Halbert 2007; Shearmur and Alvergne 2002). However, despite the relative dispersal of service activities towards the west and southwest of the first and second couronne, control activities have not left Paris intramuros (Moualert and Gallouj 1995). A similar process of intra-urban and intra-regional dispersal can be identified for London and southeast England (Pratt 2008), the large German agglomerations (Schamp 1995; Luthi, Thierstein and Goebel 2010) and the Vienna region (Todtling and Traxler 1995). In the metropolitan area of Lisbon, in contrast, APS are still strongly concentrated in the city center; so far, suburbanization has been limit- ed to trade and transport activities without APS (Ferrao and Domingues 1995). For the Nordic countries, Illeris and Sjøholt (1995, 218) found that » … only a few business services really depend on a central city location for their contacts. Most of the firms that are still located in the center are there for prestige reasons or because they appreciate the environment. However, as car accessibility deteriorates and rents increase in the urban center, they tend to shift to suburban locations.« According to the 2008 report compiled by GaWC regarding well-known city connectivity measures, Belgrade belongs to the high-sufficiency category (GaWC 2008). The GaWC research team developed a new measure of the dynamics of contemporary cities devised by the GaWC research network. Unfortunately (according to Global Buzz–The GaWC Monthly Monitor, table 2010-07), Belgrade cannot be found among the sixty-two cities studied (GaWC, 2010). Of all the cities in transition, Moscow holds the best position, and apart from Moscow the analysis includes Budapest and Warsaw. 133 Vera Gligorijevi}, Mirjana Devedì}, Ivan Ratkaj, Localization factors and development strategies for producer services: a case study … 2 Methodology In order to study the patterns of business activity in Belgrade metropolitan areas, we used descriptive case-study research. For this article it was important to select cases at three different levels: territorial selec- tion, APS sector selection, and APS firm selection. The territorial selection of the Belgrade metropolitan area comes down to spatial zoning, where two city centers have been named: the wider CBD (the tradi- tional zone of the work function agglomeration) and New Belgrade (the municipality that has been experiencing the most intensive business development since the beginning of the 1990s). The rest of the urban area is not characterized by marked growth of work function and is generally a zone of dispersed loca- tions of companies. The CBD has been statistically precisely defined combining geographical regression of work function and spatial clustering methods (Ratkaj 2009). In addition, we distinguish the »wider CBD,« a statistically defined CBD expanded using Euclid's distance (buffering) of 500 m. The aim was to indicate the existence of APS firms that gravitate towards the CBD as those located within walking dis- tance from the CBD. In this context, the wider CBD can be viewed as a functional CBD with more flexible borders. APS encompass seven sectors: advertising, finance and banking, insurance, information technology (IT), law, consulting, and accounting. Consulting incorporates several subsectors: management consulting, business consulting, design consulting, and human resource consulting. The selection of the sectors was per- formed in compliance with the analysis of polycentric European regions (Taylor, Evans and Pain 2006). The same APS sectors form the basis of the interlocking network model developed by a team of Globalization and World Cities Research Network (GaWC) researchers for studying the world city network (Taylor etal. 2009). The selection of APS firms was performed according to their rank. The sample included the best com- panies per sector ranked according to income in 2009. The availability of the data caused the samples to be unevenly distributed among sectors (Table 1). The literature suggests a sample that only consists of APS transnational corporations (TNCs). However, Belgrade's meager APS TNC sample was not enough to provide solid arguments. Therefore the sample included all foreign firms. The authors suggest that it is possible to equate foreign companies with TNCs. This supposition has been confirmed by the results of the analysis of the location of foreign APS firms in Belgrade that have the same location patterns as APS TNCs in global cities (Han and Qin 2009; Taylor et al. 2009; Hermelin 2007; Shearmur and Alvergne 2002). 2.1 Data sources All of the data were gathered from secondary sources, such as various databases, census statistics, and Serbian Business Registers Agency databases. In order to identify APS firms in Belgrade, we used a two-step pro- cedure. The first step consisted of identifying the most successful APS firms doing business in Belgrade, for which we used special publications from The Economist; in particular, Top 300 (2009) for IT firms, and Banks and Insurance Companies (2009) for finance/banking, insurance and accounting firms. We also used Taboo magazine and its review »Results of Business Activities of Marketing Communication Agencies« (2009) for advertising firms, then Chambers et al. (Chambers … 2014) for law firms, Gartner Special Reports Top 10 Consulting Services Companies for South-East Europe (Internet 1), and the Belgrade Chamber of Commerce register of consulting agencies (Internet 2). Table 1: Number of firms by sectors and capital. Sectors Number of firms Domestic Foreign Advertising 24 20 4 Finance and Banking 21 6 15 Insurance 12 6 6 IT 7 2 5 Law 19 12 7 Consultancy 28 16 12 Accountancy 18 14 4 TOTAL 129 76 53 134 Acta geographica Slovenica, 54-1, 2014 The second step consisted of checking the data for each of the firms in the Serbian Business Registers Agency national database (Internet 3). This database represents the official statistics of all firms and orga- nizations in Serbia. It provided information on firms, including type of business activity in compliance with NACE Rev. 2 codes, current status (active or inactive), prevailing capital origin (domestic or foreign), and location (address). 3 Results The findings suggest that the distribution pattern of producer services has gradually changed from dis- persed to centripetal development towards the new business district. This article defines three aspects for distinguishing and analyzing APS firms: area, capital origin, and sector. 3.1 The CBD versus New Belgrade Table 2 summarizes the data and relates them to the territorial division of the Belgrade metropolitan area. Of the total number of APS firms, 53% are located in the wider CBD. All sectors are present there except IT firms, which prefer New Belgrade or other areas. Consulting, law, and advertising firms are present in the greatest numbers, whereas there are only a small number of banks and insurance companies. Approximately 70% of the firms in the CBD were founded using domestic capital (Figure 1). Table 2: Share of sectors in the CBD and New Belgrade. Advertising Finance Insurance IT Law Consultancy Accountancy Total and Banking CBD 20,3 15,9 7,2 – 20,9 20,3 15,9 100 New Belgrade 9,1 30,3 21,2 15,1 3,1 18,2 3,1 100 Approximately 26% of the total number of APS firms analyzed are located in New Belgrade. The rest of the APS firms studied (around 20%) are dispersed outside the CBD area and New Belgrade and were not considered further. New Belgrade has all seven APS firm sectors presented, with a clear predominance of banks, insurance, consulting, and IT companies. Law firms and accounting companies are fewest in number. Over 80% of APS firms located in New Belgrade are foreign, and less than 20% were founded using domestic capital. 3.2 Domestic versus foreign firms Table 3 shows how business is distributed across the Belgrade metropolitan area in terms of whether firms are domestic or foreign. Domestic firms (founded by domestic capital) make up about 60% of the total number of APS firms in Belgrade. The structure of firms according to capital is uneven in the areas and sectors considered. In the CBD and the rest of the city areas outside New Belgrade, domestic firms are dominant, whereas foreign firms clearly dominate in New Belgrade. Table 3: Share of domestic and foreign firms in the CBD and New Belgrade. The number of APS firms Foreign firms Domestic firms Total CBD 69 30,4 69,6 100 New Belgrade 33 81,8 18,2 100 Other 27 18,5 81,5 100 Territorial distribution of domestic firms is characterized by concentration: almost 90% of domes- tic firms are located within the CBD areas, and only 10% in New Belgrade. Foreign companies (where more than 50% of the initial capital originates from abroad) are distributed in a polycentric manner: they 135 Vera Gligorijevi}, Mirjana Devedì}, Ivan Ratkaj, Localization factors and development strategies for producer services: a case study … can be found in both areas, but a little more than half of them are located in New Belgrade. In terms of sectors, foreign capital is the major capital in more than 70% of the firms dealing with banking and infor- mation technologies, half the insurance companies, and more than 40% of consulting companies. Domestic firms make up more than 80% of the total number of marketing and accounting firms, as well as more than 50% of the total number of consulting and law firms. 3.3 Sectors APS are divided into seven sectors, represented by a different number of firms (Table 1). However, the sam- ple composition according to the ownership and locational strategy of the firms sampled is far more important than their number. The results are presented for each sector separately (Figure 1). Advertising: twenty-four firms were analyzed, only four of which have foreign capital as predominant. They are territorially concentrated: 83% of advertising firms are located inside the CBD. For most of the mar- keting agencies, accessibility is top priority, which corresponds to the central city zone. The second strategy is locating the firm in relatively distant but highly prestigious zones, set outside the main public trans- port routes. New Belgrade did not prove to be an attractive location. Finance and banking: twenty-one firms were analyzed, fifteen of which have foreign capital as pre- dominant. Banks are characterized by polycentric distribution: they are almost evenly distributed among the CBD and New Belgrade. Two locational strategies were identified: location in the city center due to the importance of being accessible and centrally positioned, as well as location in New Belgrade due to the existence of open space suitable for the construction of new large buildings. However, even in New Belgrade, banks are located along main radial roads, which provide a quick link to the city center. In addi- tion, they are located near densely populated New Belgrade areas. Out of ten banks located in New Belgrade, nine have foreign capital as predominant. Advertising (domestic) Advertising (foreign) Finance and Banking (domestic) Finance and Banking (foreign) Insurance (domestic) Insurance (foreign) IT (domestic) IT (foreign) Law (domestic) Law (foreign) Consultancy (domestic) Consultancy (foreign) Accountancy (domestic) Accountancy (foreign) Statistically Defined CBD Wider CBD (buffer zone) 0 1 2 4 km New Belgrade Figure 1: Location choices of firms, by sector and ownership. 136 Acta geographica Slovenica, 54-1, 2014 Figure 2: New bridge on the Sava River. Line 1 Line 2 Line 3 Depot line 0 1 2 4 km Station Figure 3: Belgrade subway plan – not yet under construction. Insurance: twelve firms were analyzed, six of which have foreign capital as predominant. They are locat- ed in New Belgrade, with seven of them (six foreign) located in the CBD or zones gravitating towards it as well. The locational strategy is similar to the one the banks have, and foreign companies find New Belgrade especially attractive. Transport accessibility is also important. 137 Vera Gligorijevi}, Mirjana Devedì}, Ivan Ratkaj, Localization factors and development strategies for producer services: a case study … IT: Seven firms were analyzed, five of which have foreign capital as predominant. They are mostly locat- ed in New Belgrade (five firms, four of which are foreign). None of them are located inside the CBD or its immediate vicinity. Four firms are located near the freeway. The two companies located near the har- bor are not oriented to the domestic market, and so their ability to reach the local population via thoroughfares is not significant. Law: nineteen firms were analyzed, seven of which have foreign capital as predominant. Only one (for- eign) law firm is located in New Belgrade, whereas fourteen of them are located inside the CBD or a zone gravitating towards it. Centrality – that is, being accessible to the local market – is an extremely impor- tant factor for their location. The size of the premises is of no importance. Consulting: twenty-eight firms were analyzed, twelve of which have foreign capital as predominant. They are mostly located in the CBD or in a zone gravitating towards it. There are only six consulting agen- cies in New Belgrade, all of which are foreign. Centrality is also important for their location, but foreign companies clearly recognize the attractiveness of New Belgrade. Accounting: eighteen firms were analyzed. Four of them have foreign capital as predominant and most are located in the CBD or a zone gravitating towards it. Accounting companies can also be found in other city regions (six are located outside the wider CBD and New Belgrade). Unlike consulting companies, all accounting companies are located inside the CBD. 4 Discussion and conclusion First, the high level of concentration of APS at the national level in the Belgrade metropolitan area was affected by several factors: the high-order position inherited from the settlement network of the former Socialist Federal Republic of Yugoslavia (SFRY) and Federal Republic of Yugoslavia (FRY), particularly the position of the capital city; the concentration of human capital; and the concentration of direct for- eign investments. Important factors to increase APS in Belgrade were transition towards a market economy and economic globalization, and also strategic government decisions towards a knowledge-based econ- omy, which later caused occupational structure changes (Gligorijevi} 2009). The second conclusion of the APS pattern analysis is the high level of concentration in the CBD, sim- ilar to other large European cities. Urban amenities certainly play a major role in the preference of high-order functions for the CBD (Todtling, Lehner and Trippl 2006; Tonts and Taylor 2010; Wu 2003), which is close- ly related to prestige and place symbolism. The analysis by Castells (1989) shows that the CBD has a concentration of APS firms, and that the reasons for this lie in the need for face-to-face contact, a busi- ness social milieu with a unique culture, a prestigious location, existing office stock, and available ancillary services. The third result of the research is recognition of intra-urban multipolar development. In the first phas- es of APS development in Belgrade, APS firms were concentrated in the CBD, and later on some firms dispersed around it. Findings suggest that the distribution pattern of producer services has gradually changed from dispersed to concentrated in the new business center: New Belgrade. It has fewer amenities than the CBD, but it attracts foreign firms and investments. The traditional CBD is still an important residential zone, with a lack of modern business space, which influenced the business shift towards New Belgrade. The advantages of New Belgrade, in comparison to the CBD, include modern transport infrastructure, vicinity of the airport and the highway, the absence of denationalization issues, and extensive open space. From a socially relatively uniform »large dormitory« under communism, New Belgrade has transformed into a new business center marked by more prominent social stratification (Petrovi} 2000). Concentration of business facilities in selected zones of New Belgrade presupposes the influx and concentration of the new service class, for which high-quality residential buildings have been built. Based on interviews conduct- ed with experts from the Institute of Architecture and Urban and Spatial Planning of Serbia, Barlov (2009) discusses » the obsession with business-residential construction« and the domination of » investment urban- ism« and greenfield investments, and points out that a rapid urban transformation of New Belgrade is underway, leading to the gradual destruction of the functional city aspirations for the needs of the busi- ness interests of the minority. The development of New Belgrade was also influenced by abandoning the centralized planning sys- tem and introducing neoliberal capitalism. These changes led to severe collapse of the monocentric structure 138 Acta geographica Slovenica, 54-1, 2014 of communist Belgrade. The urban development of New Belgrade is not a controlled and planned coun- terpart to the CBD, but an embodiment of the market economy. Urban experts face many challenges, but the biggest of all is to reduce the traffic volume and to improve connectivity between the old and new parts of Belgrade. A temporary solution to this problem is the construction of a new bridge on the Sava River (Figure 2) and designing a subway (Figure 3). In addition, New Belgrade's population increase requires social policy improvements, especially investment in schools and hospitals, regardless of the economic effects of these investments. 5 Acknowledgment This article contains research findings from projects nos. 176017 and 47006, supported by the Serbian Ministry of Education, Science, and Technological Development. 6 References Banks and insurance companies. Special edition, Economist, 2009. Belgrade. Bassens, D., Derudder, B., Taylor, P. J., Pengfei, N., Hoyler, M., Huang, J., Witlox, F. 2010: World city net- work integration in the Eurasian realm. Eurasian geography and economics 51-3. DOI: http://dx.doi.org/ 10.2747/1539-7216.51.3.385 Barlov, S. 2009: Transformacija jednog grada – Novi Beograd. Internet: http://pescanik.net/2009/09/trans- formacija-jednog-grada-%E2%80%93-novi-beograd/ (1. 9. 2009). Bourdeau-Lepage, L., Huriot, J. M. 2005: On poles and centers: Cities in the French style. Urban public economic review 3. Castells, M. 1989: The informational city. Oxford. Castells, M. 1996: The rise of the network society. Oxford. Chambers Europe publication. Internet 1: http://www.chambersandpartners.com/Europe/Search/Location/ 185. n (17. 2. 2012) Coffey, W. J. 1995: Producer services research in Canada. Professional geographer 47. Daniels, P. W.1995: The locational geography of advanced producer services firms in the United Kingdom. Progress in planning 43, 2-3. DOI: http://dx.doi.org/10.1016/0305-9006(95)96164-M Ferrao, J., Dominigues, A. 1995: Portugal: The territorial foundations of a vulnerable tertiarisation process. Progress in planning 43, 2-3. DOI: http://dx.doi.org/10.1016/0305-9006(95)96171-M GaWC, 2008: The World according to GaWC. Internet: http://www.lboro.ac.uk/gawc/world2008t.htm (1. 9. 2009). GaWC, 2008: The GaWC monthly monitor, global buzz. Internet: http:/ www.lboro.ac.uk/gawc/globalbuzz.html (1. 9. 2009). Gligorijevic, V. 2009: Demografska obelèja radne snage u Beogradu po~etkom XXI veka. Demografija 6. Beograd. Halbert, L. 2004: The decentralization of intrametropolitan business services in the Paris region: Patterns, interpretation, consequences. Economic geography 80-4. DOI: http://dx.doi.org/10.1111/j.1944- 8287.2004.tb00244.x Halbert, L. 2007: From sectors to functions: producer services, metropolization and agglomeration forces in the Ile-de-France region. Belgeo 1. Hall, P., Pain, K. 2006: From metropolis to polyopolis. The polycentric metropolis: learning from mega-city regions in Europe. Sterling. Hall, P. 2004: Polycentricity: concept and measurement. Polynet discussion paper. Hall, P. 2001: Global city-regions in the twenty-first century. Global city regions: trends, theory, policy. New York. Han, S., Qin, B. 2009: The spatial distribution of producer services in Shanghai. Urban Studies 46. DOI: http://dx.doi.org/10.1177/0042098009102133 Hermelin, B. 2007: The urbanization and suburbanization of the service economy: producer services and specialization in Stockholm. Geografiska Annaler B – Human geography 89. DOI: http://dx.doi.org/ 10.1111/j.1468-0467.2007.00260.x 139 Vera Gligorijevi}, Mirjana Devedì}, Ivan Ratkaj, Localization factors and development strategies for producer services: a case study … Illeris, S., Sjohot, P. 1995: The Nordic countries: High quality service in a low density environment. Progress in planning 43, 2-3. DOI: http://dx.doi.org/10.1016/0305-9006(95)96169-R Internet 1: http://www.deloitte.com/assets/Dcom-Global/Local%20Assets/Documents/Press/deloitte_ vol2_article3.pdf (27. 6. 2012). Internet 2: http://217.24.23.93/Aplikacije.aspx?aplikacija=konsultantskeKuce (2. 4. 2012). Internet 3: http://pretraga2.apr.gov.rs/ObjedinjenePretrage/Search/Search (8. 4. 2012). Lundquist, K-J., Oland, L-O., Henning, M. 2008: Producer services: growth and roles in long term economic development. The Service Industries Journal 28-4. DOI: http://dx.doi.org/10.1080/02642060801917588 Luthi, S., Thierstein, A., Goebel, V. 2010: Intra-firm and extra-firm linkages in the knowledge economy: the case of the emerging mega-city region of Munich. Global networks 10. DOI: http://dx.doi.org/ 10.1111/j.1471-0374.2010.00277.x Moulaert, F., Todtling, F. 1995: The role of transnational corporations. Progress in planning 43. DOI: http://dx.doi.org/10.1016/0305-9006(95)96163-L Moulaert, F., Gallouj, C. 1995: Advanced producer services in the french space economy: Decentralisation at the highest level. Progress in planning 43. DOI: http://dx.doi.org/10.1016/0305-9006(95)96165-N Musil, J. 1993: Changing urban sistems in post-comunists societies in Central Europe: analysis and pre- diction. Urban studies 30-6. DOI: http://dx.doi.org/10.1080/00420989320080841 Petrovic, M. 2000: Gradovi u tranziciji: iskustva razvijenih zemalja u poslednjim decenijama 20. veka. Sociologija 42-3. Pratt, A. 2008: Questioning the relationship between advanced producer services, the cultural industries and global cities. L'économie culturelle et ses territoires. Toulouse. Ratkaj, I. 2009: Prostorno-funkcionalna organizacija Beograda. Beograd. Taboo magazine. Review »Results of business activities of marketing communication agencies«, 2012, Beograd. Sassen, S.1991: The global city: New York, London, Tokio. Princeton. Sassen, S. 2001: Global cities and global city regions: a comparison. Global city regions: trends, theory, policy. Oxford. Shearmur, R., Alvergne, C. 2002: Intrametropolitan patterns of high-order business service location: A com- parative study of seventeen sectors in Ile-de-France. Urban Studies 39-7. DOI: http://dx.doi.org/10.1080/ 00420980220135536 Schamp, E. W. 1995. The geography of APS in a goods exporting economy: The case of West Germany. Progress in planning 43. DOI: http://dx.doi.org/10.1016/0305-9006(95)96166-O Stein, R. 2002: Producer services, transaction activities and cities: rethinking occupational category in eco- nomic geography. European planning studies 10-6. DOI: http:/ dx.doi.org/10.1080/0965431022000003780 Szelenyi, I.1996: Cities under socialism – and after. Cities after Socialism: Urban and regional change and conflict in post-socialist countries. Oxford. Taylor, P. J. 2004: World City Network. London. Taylor, P. J., Evans, D., Pain, K. 2006: Organization of the polycentric metropolis: corporate structures and networks. The polycentric metropolis: Learning from the mega-city regions in Europe. Sterling. Taylor, P., Evans, D., Hoyler, M., Derudder, B. and Pain, K. 2009: The UK space economy as practiced by advanced producer service firms: identifying two distinctive polycentric city-regional processes in con- temporary Britain. International journal of urban & regional research 33-3. DOI: http://dx.doi.org/ 10.1111/j.1468-2427.2009.00857.x Todtling, F., Lehner, P. and Trippl, M. 2006: Innovation in knowledge intensive industries: the nature and geography of knowledge links. European planning studies 14-8. DOI: http://dx.doi.org/10.1080/ 09654310600852365 Todtling, F., Traxler, J. 1995: The changing location of advanced producer services in Austria. Progress in planning 43. DOI: http://dx.doi.org/10.1016/0305-9006(95)96168-Q Tonts, M., and Taylor, M. 2010: Corporate location, concentration and performance: large company headquarters in the Australian urban system. Urban Studies 47-12. DOI: http://dx.doi.org/10.1177/ 0042098009359029 Top 300, Special edition magazin Econom:east, 2009. Beograd. Wu, F. 2003: Globalization, place promotion and urban development in shanghai. Journal of urban affairs 1-25. DOI: http://dx.doi.org/10.1111/1467-9906.00005 140 Acta geographica Slovenica, 54-1, 2014 ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKI ZBORNIK 2014 SPECIAL ISSUE NATURAL HAZARDS 2014 EDITORS: Slobodan B. Markovi} Blà Komac Matija Zorn 141 142 Acta geographica Slovenica, 54-1, 2014, 143–161 MODELING OF THE ARAL AND CASPIAN SEAS DRYING OUT INFLUENCE TO CLIMATE AND ENVIRONMENTAL CHANGES Slobodan B. Markovi}, Albert Ruman, Milivoj B. Gavrilov, Thomas Stevens, Matija Zorn, Blà Komac, Drago Perko The Caspian sea (Credit: NASA). Modelling of the Aral and Caspian seas drying out influence to climate and environmental changes Modelling of the Aral and Caspian seas drying out influence to climate and environmental changes DOI: http://dx.doi.org/10.3986/AGS54304 UDC: 911.2:551.588(5-191.2) COBISS: 1.01 ABSTRACT: The complete drying out of the Aral and Caspian seas, as isolated continental water bodies, and their potential impact on the climate and environment is examined with numerical simulations. Simulations use the atmospheric general circulation model (ECHAM5) as well as the hydrological discharge (HD) model of the Max-Planck-Institut für Meteorologie. The dry out is represented by replacing the water surfaces in both of the seas with land surfaces. New land surface elevation is lower, but not lover than 50 m from the present mean sea level. Other parameters in the model remain unchanged. The initial meteoro- logical data is real; starting with January 1, 1989 and lasting until December 31, 1991. The final results were analyzed only for the second, as the first year of simulation was used for the model spinning up. The drying out of both seas leads to an increase in land surface and average monthly air temperature dur- ing the summer, and a decrease of land surface and average monthly air temperature during the winter, above the Caspian Sea. The greatest difference in temperature between dry and not dry cases have the same values, about 7–8 °C in both seasons, while daily extremes of temperature are much more pronounced. In the wider local/regional area, close to both seas, drying out leads to a difference in average annual temperatures by about 1 °C. On a global scale, the average annual temperature remains unchanged and the configuration of the isotherms remain unchanged, except for over some of the continents. In winter, Central Asia becomes cooler, while over Australia, southern Africa, and South America, it becomes slight- ly less warm. Furthermore, a new heat island occurs in western Sahara during summer. KEY WORDS: Caspian Sea, Aral Sea, drying out, numerical simulation, air temperature, climate change The article was submitted for publication on April 3, 2013. ADDRESSES: Slobodan B. Markovi}, Ph. D. Chair of Physical Geography, Department of Geography, Tourism and Hotel Management Faculty of Sciences, University of Novi Sad Trg Dositeja Obradovi}a 3, RS – 21000 Novi Sad, Serbia E-mail: slobodan.markovicadgt.uns.ac.rs Albert Ruman, M. Sc. Republic Hydrometeorological Service Kneza Vi{eslava 66, RS – 11000 Beograd, Serbia E-mail: albert.rumanahidmet.gov.rs Milivoj B. Gavrilov, Ph. D. Chair of Physical Geography, Department of Geography, Tourism and Hotel Management Faculty of Sciences, University of Novi Sad Trg Dositeja Obradovi}a 3, RS – 21000 Novi Sad, Serbia E-mail: milivoj.gavrilovayahoo.com Thomas Stevens, Ph. D. Centre for Quaternary Research, Department of Geography Royal Holloway, University of London Egham, Surrey TW20 0EX, UK E-mail: Thomas.Stevensarhul.ac.uk 144 Acta geographica Slovenica, 54-1, 2014 Matija Zorn, Ph. D. Anton Melik Geographical Institute Research Centre of the Slovenian Academy of Sciences and Arts Gosposka ulica 13, SI – 1000 Ljubljana, Slovenia E-mail: matija.zornazrc-sazu.si Blà Komac, Ph. D. Anton Melik Geographical Institute Research Centre of the Slovenian Academy of Sciences and Arts Gosposka ulica 13, SI – 1000 Ljubljana, Slovenia E-mail: blaz.komacazrc-sazu.si Drago Perko, Ph. D. Anton Melik Geographical Institute Research Centre of the Slovenian Academy of Sciences and Arts Gosposka ulica 13, SI – 1000 Ljubljana, Slovenia E-mail: dragoazrc-sazu.si 145 Modelling of the Aral and Caspian seas drying out influence to climate and environmental changes 1 Introduction Since the beginning of Earth's history, climate has varied (Goosse et al. 2013). Its climate system is affected by many factors that can be classified into three major groups: • astronomical factors, such as solar or Earth orbital variability; • natural landscape factors, such as spatial distribution of land and sea, configuration and type of land surface, vegetation cover and • anthropogenic factors, such as atmospheric composition and land use. The latter influences climate only in recent centuries (e.g. Dahan 2010). The study of current/recent climate change is focused on two main themes: • the net overall climate change and • constraining the relative influences of natural versus anthropogenic influences (Hansen and Sato 2012). This paper examines the potential impact of the drying out of the Aral and Caspian seas on local, region- al, and global climate and environment. In the case of the Aral Sea's recent progressive drying out process is mostly triggered only by anthropogenic factors. Current human influence on the hydrological regimes in catchments of the Aral Sea results in its reduced surface and volume (Peneva et al. 2004; Toman 2013), leading to its immanent final disappearance. In the case of Caspian Sea the human influence has not been so severe, although the sea level drop caused by big contractions on Volga River are reported since the 1950s (Vri{er 1953). Thus the disappearance of the Caspian Sea can be significantly accelerated in the case of major inflow decrease of water from the main tributaries, the Volga and Ural rivers. On the other hand, also natural influence on the hydrological regimes in the catchment of the Caspian Sea has been observed. The Caspian Sea is subject to large variations in the amount of water and water surface, as it was during the Late Pleistocene and postglacial periods (Kislov et al. 2012). Without going into the details of all of these processes, our study introduces a presumption that the drying out of the Aral and Caspian seas has happened in the last decades. The influence of drying out on air temperature will be considered. Beside the impact on the climate, the drying out of the inland seas would impact the environment and ultimately the human society. It is a widely accepted view that the roots of today's civilization are linked to ancient human societies that existed in the valleys of major rivers, such as the Nile in Africa, the Tigris and Euphrates rivers in the Middle East, the Indus in South Asia, and the Yangtze and Yellow rivers in China. Many civilizations took advantage of natural flooding of rivers for agricultural development, and later developed irrigation and flooding control to further enhance farming conditions (Diamond 2005). Water management should be planned, including digging of channels to organize work in the fields, keeping accurate records, tak- ing care of security, implementing control, synchronizing decisions and transmitting orders. Economy was subordinated to the very complex interface between human organization and management. Over time, these teams ensured the emergence and development of civilizations in the river valleys. Civilizations based on good water management survived the longest of all in the past, and are sometimes referred to as »hydraulic civilizations« (Gavrilov 2005). Multi millennial experience in water management has mainly brought bless- ings. Until recently, people did not notice the consequences of bad management. 1.1 Aral Sea The Aral Sea is lying between Kazakhstan in the north and Uzbekistan in the south. It is a completely enclosed basin with a large inland catchment area. Most of the surrounding land is desert and almost all water enter- ing the basin comes from two major rivers: Amu Darya and Sir Darya (Peneva et al. 2004; Toman 2013). The name of the Aral Sea roughly translates from old Turkish as »Sea of Islands«, referring to the more than 1,534 islands that once dotted its waters. Previously it was the fourth largest lake in the world with an area of 68,000 km2 (Figure 1). The Aral Sea has been steadily shrinking since the 1960s after the Amu Darya and Sir Darya Rivers were diverted by Soviet irrigation projects. By 2007, it had declined to 10% of its original size, splitting into four lakes: the North Aral Sea, the eastern and western basins of the once far larger South Aral Sea, and one smaller lake between the North and South Aral Sea (Micklin and Aladin 2008). By 2009, the southeastern lake had disappeared and the southwestern lake retreated into a smaller water bodies at the far west of the former southern sea (Singh et al. 2012; Figure 2). 146 Acta geographica Slovenica, 54-1, 2014 The shrinking of the Aral Sea has been called one of the planet's worst environmental disasters. The region's once prosperous fishing industry has been essentially destroyed, bringing unemployment and economic hardship. The Aral Sea region is also heavily polluted, with resulting serious public health problems. The retreat of the sea has reportedly also caused local climate change, with summers becom- ing hotter and drier, and the winters becoming colder and longer (Micklin 2007). 1.2 Caspian Sea The Caspian Sea is situated in a semi-arid area between southern Russia, Kazakhstan, Turkmenistan, Iran and Azerbaijan (36°–47° N, 47°–54° E) and currently lies 27 m below sea level. It is the world's largest inland body of water without a connection to the world oceans, with a surface area of 390,000 km2 and volume of 66,100 km3 (Figure 3). It is a reservoir of brackish waters, highly sensitive to climate changes. It has large catchment area of approximately 3.5 million km2 (Arpe and Leroy 2007; Arpe et al. 2012). The salinity of the Caspian Sea varies from the north to the south from 1.0 to 13.5 ‰. This difference is most marked in the north due to the freshwater supplied by the Volga River. In other areas, average water salinity is 12.5 ‰ (Dumont 1998). The Caspian Sea is divided into three basins but differing in depth and volume: the south (water depth up to < 1020 m), middle (< 900 m) and north (< 15 m) basins, which represent two-thirds, one-third and 1% of the total volume of water, respectively. The Caspian Sea was formed in the Pliocene, about 3 million years ago, after its separation from the Black and Pannonian seas. From that time, due to specific geomorphological conditions, it has experienced numerous transgressions and regressions with water level fluctuations of several tens of meters (Varuschenko et al. 1987), causing important changes in its shoreline, particulary in the north (Tudryn et al. 2013). The current environmental changes experi- enced in the area, especially the negative water budget in the northern and eastern shallow parts of Caspian Sea, indicate serious consequences. 2 The model The atmospheric general circulation model ECHAM5 (Roeckner et al. 2003) was used for simulations presented in this study. This fifth-generation atmospheric general circulation model developed at the Max-Planck-Institut für Meteorologie (MPIM) in Germany is the most recent version in a series of ECHAM model versions evolving originally from the spectral weather prediction model of the European Centre for Medium Range Weather Forecasts (ECMWF), (Simmons et al. 1989). The ECHAM5 is well designed for climatological studies (Roeckner et al. 2004), because there are many good solutions in numerics and physics of the model. It is important to note that a hydrological discharge model (Hagemann and Dümenil 1996; 1998; Hagemann et al. 2006), developed at MPIM, is included in the ECHAM5 model. Also, ECHAM5 has been used for research similar to these (e.g. Kislov et al. 2012). The horizontal resolution (spectral transaction) of the ECHAM5 model is T42 (128 × 64 grid point or 221 × 221 km on latitude 45°), the model had 19 vertical layers and a time step of 1800 s. Other para- meters of model were standardized and/or adapted to the capacities of computer used. 3 Geographical areas The model used two types of global geographical areas. The first is the original geographical area, as used in the basic version model ECHAM5. This area is marked with G1. Part of G1 around the Aral and Caspian seas labelled as area A1, (32.1°–60.0° N, 39.3°–67.5° E) is shown in Figure 5. The area A1 shows a distinct geographic configuration of land and sea on the surface and state bor- ders before the collapse of the Soviet Union (the green lines) all around the Aral and Caspian seas. Also, A1 shows the values of the lake mask (LM) in equidistant grid points. Lake mask is a special value in ECHAM5, which is the ratio of areas of land and water per a box in the grid points, but only on the main- land (Hagemann 2002). LM takes values between 0 and 1, as markers for land 100% and for water 100%, all on the land, respectively. It should be noted that there is no value LM over the oceans and seas. Second type of global geographical area is the modified geographical area, marked as G2. Part of G2 around the Aral and Caspian seas, previously marked as A1, is shown in Figure 6. 147 Modelling of the Aral and Caspian seas drying out influence to climate and environmental changes EITLLETA SECNASISANNOCE RA660 9-5H KECRO FIR . A.SU Figure 1: The Aral Sea in the year 1964 (Credit: NASA Earth Observatory). 148 Acta geographica Slovenica, 54-1, 2014 ASAN Figure 2: The Aral Sea in the year 2009 (the black line shows the extend of the Aral Sea in the year 1960; Credit: NASA Earth Observatory). 149 Modelling of the Aral and Caspian seas drying out influence to climate and environmental changes ASAN Figure 3: The Caspian Sea is the world's largest inland body of water (Credit: NASA Earth Observatory). 150 Acta geographica Slovenica, 54-1, 2014 Horizontal Grid (Latitude-Longitude) Vertical Grid (Height or Pressure) Physical Processes in a Model Figure 4: Schematic representation of the main components of the numerical model of the atmosphere (Internet 1). Besides horizontal (latitude-longitude) grid and vertical (height or pressure) grids in spherical geometry (Earth globe), can be seen the most important physical processes in the atmosphere, continents and oceans, such as solar and terrestrial radiation, advection, momentums, heat, water, clouds, precipitations, sea ice and mixed layer ocean. All the above mentioned components and processes are connected to natural laws, which are described by mathematical equations, whose are solutions obtain on the computers by using the initial data of the atmosphere, oceans and continents, and finally after a lot of calculations the output data are obtain as results of the model (Gavrilov et al. 2011). G2 is identical to G1, but has the new values of the lake mask (LM) in a rectangular frame, marked as A2, (34.8°–48.8° N, 45.0°–64.7° E) that is embedded in A1. The area A2 was developed for the purposes of numerical simulation of the drying out of the Aral and Caspian seas. The drying out is achieved by putting 0 in all grid points in A2, making both seas disappear. Besides these, other changes in the model have not been carried out. 4 Data In all cases the same initial set of global data from 1 January 1989 was used (ERA40 Reanalyse Data 01/01/1989). For this data an initialization procedure (e.g. Wiin-Nielsen 1978) was applied that adjusted the data to each other and on the normal/actual geographical area (G1). Therefore, the initial data had to be adjust- ed to the changing (modified) geographical area (G2). 5 Simulations Only one numerical simulation was run for each of the two types of geographical areas: G1 and G2. It is clear that when geographical area G1 is used, both the Aral and Caspian seas are in the model. In con- trast when geographical area G2 is used, both seas were omitted from the model. Both simulations were carried out for two years until 31 December 1991. The first year of simulation was used for the model 151 Modelling of the Aral and Caspian seas drying out influence to climate and environmental changes Grid model data at resolution T42 Original Lake Mask [fractional] 0.00 0.00 0.00 0.00 0.07 0.05 0.00 0.00 0.01 0.04 0.02 0.04 0 51.62N 0.00 0.00 0.00 0.03 0.03 0.00 0.00 0.00 0.00 0.02 0.02 0.00 0 48.84N 0.01 0.00 0.04 0.04 0.01 0.01 0.00 0.00 0.00 0.02 0.00 0.00 0 46.05N 0.00 0.00 0.03 0.00 0.33 0.67 0.15 0.00 0.39 0.20 0.00 0.00 0 43.25N 0.00 0.00 0.00 0.00 0.58 0.79 0.07 0.00 0.24 0.04 0.00 0.00 0 40.46N 0.00 0.00 0.00 0.02 0.04 0.93 0.35 0.00 0.00 0.02 0.00 0.02 0 37.67N 0.00 0.02 0.06 0.07 0.06 0.73 0.55 0.00 0.00 0.00 0.01 0.01 0 34.88N 0.00 0.00 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 32.09N 0.00 0.00 0.01 0.01 0.02 0.00 0.00 0.00 0.00 0.02 0.00 0.00 0 39.38E 42.19E 45.00E 47.81E 50.62E 53.44E 56.25E 59.06E 61.88E 64.69E 67.50E Figure 5: Area A1 as part of normal global geographical area (G1) in model ECHAM5 around the Aral and Caspian seas, showing the original lake mask (LM). spinning up, while data from the second year was used for analysis. It is considered that this simulation of the entire climatological season is sufficient for adjustment to new conditions. 6 Results and analysis All output data models are produced for both simulations with original (G1), and modified (G2) geographical areas. For this purpose, only air temperature is considered as the main climatic parameter. The temperature will be displayed in two cases; as a local/regional and as a global and continental indicator of climate change. 6.1 Local and regional impact To investigate local/regional changes in the vicinity of both the Aral and Caspian seas, two parameters were used. One parameter is the average monthly temperature for January and August at two levels (at the surface and 100 m above it) along the meridian of longitude 50.625E. 152 Acta geographica Slovenica, 54-1, 2014 Grid model data at resolution T42 New lake mask [fractional] 0.00 0.00 0.00 0.00 0.07 0.05 0.00 0.00 0.01 0.04 0.02 0.04 0 51.62N 0.00 0.00 0.00 0.03 0.03 0.00 0.00 0.00 0.00 0.02 0.02 0.00 0 48.84N 0.01 0.00 0.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 46.05N 0.00 0.00 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 43.25N 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 40.46N 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0 37.67N 0.00 0.02 0.06 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0 34.88N 0.00 0.00 0.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 32.09N 0.00 0.00 0.01 0.01 0.02 0.00 0.00 0.00 0.00 0.02 0.00 0.00 0 39.38E 42.19E 45.00E 47.81E 50.62E 53.44E 56.25E 59.06E 61.88E 64.69E 67.50E Figure 6: Area A1 as part of modified global geographical area (G2) around the Aral and Caspian seas, showing the new lake mask (LM) in the rectangular frame labelled as A2. The average monthly temperature for January and August at both levels can be seen in Figures 7–10, respectively. Green indicates the temperature distribution in the original geographic area (G1), and red is the temperature in the modified geographic area (G2). As shown in Figures 7 and 8, draining the Aral and Caspian seas leads to a decrease in January tem- perature at both levels along the longitudinal direction (50.625E). The greatest difference in temperature is about 7–8 °C around the centre line, and north and south of the centre line the difference in temper- ature monotonically decreases to about 1–2 °C in both cases. The lines are approximately matched at both levels. As can be seen, draining of the lakes reduces average monthly temperature during winter for about 8 °C, while the daily extremes of temperature drop may be much higher. As shown in Figures 9 and 10, draining of the Aral and Caspian seas leads to an increase in temperature during August at both altitude levels along the longitudinal direction (50.625E). The greatest difference in surface temperature is about 7–8 °C in the regions from 37.67 to 43.25° N. The greatest differences in tem- perature are similar in height, with the exception of 40.46° N, where the difference is less than 2 °C. At the southern and northern ends of the longitudinal direction (50.625E), temperature differences disappear. Lines are approximately matched at both levels. Draining both of the lakes increases average monthly tem- perature during the summer for about 8 °C, while the daily extremes of temperature rise may be much greater. 153 Modelling of the Aral and Caspian seas drying out influence to climate and environmental changes 1 Mean monthly Surface Temperature [C]; JAN1990 Normal lake mask LON=50.625E; LAT=from 32N to 55N 2 Mean monthly Surface Temperature [C]; JAN1990 Drainage lake mask LON=50.625E; LAT=from 32N to 55N 8 6 4 2 0 –2 –4 –6 –8 –10 –12 –14 32.09N 34.88N 37.67N 40.46N 43.25N 46.04N 48.83N 51.62N 54.42N Figure 7: Surface average monthly temperature for January. Another parameter of change is the average surface annual temperature in A2, as a local indicator, and in A1, as a regional indicator for both simulations. The values of these temperatures can be seen in Table 1. Table 1: Average annual surface temperature in areas A1 and A2 for simulations G1 and G2. G1 G2 A2 14.73 °C 13.82 °C A1 11.67 °C 10.51 °C As shown in Table 1, draining the Aral and Caspian seas leads to an overall decrease in average annu- al surface temperature in both areas. Since the difference in temperature is slightly greater in area A1, it is considered that draining both lakes have a greater impact on the local rather than regional climate. 6.2 Potential global impact In the second case, as global and continental indicator of climate change, we used two parameters. One parameter of change was the average annual global surface temperature. This temperature was the same, 154 Acta geographica Slovenica, 54-1, 2014 1 Mean monthly Air Temperature [C] at level 100 [m] ; JAN1990 Normal lake mask LON=50.625E; LAT=from 32N to 55N 2 Mean monthly Air Temperature [C] at level 100 [m] ; JAN1990 Drainage lakes LON=50.625E; LAT=from 32N to 55N 14 12 10 8 6 4 2 0 –2 –4 –6 –8 –10 –12 –1432.09N 34.88N 37.67N 40.46N 43.25N 46.04N 48.83N 51.62N 54.42N Figure 8: 100 m above average monthly temperature for January. 15.1 °C, for both simulations. As such, according to the model, draining the Aral and Caspian seas had no effect on the average annual global surface temperature. However, another set of parameters of change are the global distribution of average monthly surface temperatures for particular months, in this case January and August. These temperatures are shown on maps in Figures 11–14. As shown in Figures 11 and 12, draining the Aral and Caspian seas lead to significant differences in temperature distribution over Asia during January. In the case of G1, the zero isotherm meanders through the middle of area A1, while in the case of G2 the zero isotherm has a zonal slope and extends to the south, almost to 30° N. Also, in the case of G1, the –20 °C isotherm is located in NE Asia to NW–SE direction, while in the case of G2 this isotherm penetrates the centre of the continent. It can be concluded that the removal of both seas lead to cooling of Asia during winter. By contrast, the configuration of isotherms in other parts of the world remains nearly unchanged. It may be noted that the warmest areas in Australia, southern Africa and South America are less pronounced in G2 than in G1. As shown in Figures 13 and 14, draining the Aral and Caspian seas does not significantly change the con- figuration of August isotherms, but it does change the distribution of the hottest areas in Asia and Africa. In the case of the G2 simulation, on the locations of the Aral and Caspian seas is becoming warmer. Also, in addition to the three areas of extreme high temperatures in Asia (two in the Arabian Peninsula and third in Kashmir), there are additional areas of extreme temperatures in the western Sahara. Another sig- nificant trend is the cooling of the Tibetan plateau to a greater extent than the surrounding regions. 155 Modelling of the Aral and Caspian seas drying out influence to climate and environmental changes 1 Mean monthly Surface Temperature [C]; AUG 1990 Normal lake mask LON=50.625E; LAT=from 32N to 55N 2 Mean monthly Surface Temperature [C]; AUG 1990 Drainage lake mask LON=50.625E; LAT=from 32N to 55N 36 34 32 30 28 26 24 22 20 18 16 14 32.09N 34.88N 37.67N 40.46N 43.25N 46.04N 48.83N 51.62N 54.42N Figure 9: Surface average monthly temperature for August. 7 Discussion and conclusion We evaluated climate and environmental changes in the case of a complete drying out of the two large inland seas of the Aral and Caspian seas, located in arid and semiarid continental areas. This kind of sce- narios are quite plausible, as the Aral Sea is already almost completely dried up, while shallow parts of the Caspian Sea are being transformed into terrestrial ecosystems. As such, it is important to model the effects on both local and regional/global conditions. The modelling results using the ECHAM5 model are quite dramatic. Comparing the temperature changes it was found that the drying out of both the Aral and Caspian seas leads to an increase in sum- mer and decrease in winter average monthly temperature by the similar amount, from about 7–8 °C, while the daily extremes of temperature may be even more pronounced. In the wider regional zone, close to both seas, the average annual temperature is reduced by about 1 °C. However, at the global scale, average annual temperature remains unchanged, while the general configuration of the isotherms remains unchanged, except for some shifts over the continents. Presented approach can also be applied to paleoclimatic research. Spatial and temporal changes of the Paratethys Basins can be regarded as a key factor responsible for Cenozoic climate changes (Ramstein etal. 1997). The results of this study demonstrate that the drying out of isolated sea basins such as the described ones can cause significant regional climatic and environmental changes. Similar was shown for the drying out 156 Acta geographica Slovenica, 54-1, 2014 1 Mean monthly Air Temperature [C] at level 100 [m] ; AUG 1990 Normal lake mask LON=50.625E; LAT=from 32N to 55N 2 Mean monthly Air Temperature [C] at level 100 [m] ; AUG 1990 Drainage lakes LON=50.625E; LAT=from 32N to 55N 48 46 44 42 40 38 36 34 32 30 28 26 24 22 20 18 16 14 12 32.09N 34.88N 37.67N 40.46N 43.25N 46.04N 48.83N 51.62N 54.42N Figure 10: 100 m above average monthly temperature for August. of Mediterranean Basin (Murphy et al. 2009), or drying out of Paratethys Basins, e.g. the present Pannonian Basin (Hamon et al. 2013). 8 Acknowledgments This research paper is financed by Project 176020 of the Serbian Ministry of Education, Science and Technological Development and Project 114-451-2670 of Secretariat of Science and Technological Development of Vojvodina province government. The authors are grateful for the support of Slobodan Ni~kovi} and Valentina Janc. 9 References Arpe, K., Leroy, S. A. G. 2007: The Caspian Sea Level forced by the atmospheric circulation, as observed and modelled. Quaternary international 173–174. DOI: http://dx.doi.org/10.1016/j.quaint.2007.03.008 Arpe, K., Leroy, S. A. G., Lahijani, H., Khan, V. 2012: Impact of the European Russia drought in 2010 on the Caspian Sea level. Hydrology and earth system science 16. DOI: http://dx.doi.org/10.5194/ hess-16-19-2012 157 Modelling of the Aral and Caspian seas drying out influence to climate and environmental changes Forecast mean surface temperature C JAN 1990 Normal lake mask 180 90W 0 90E 180 60N 60N 30N 30N EQ EQ 30S 30S 60S 60S 180 90W 0 90E 180 –50 –40 –30 –20 –10 0 10 20 30 40 50 Figure 11: Global distribution of surface average January temperatures in G1. Forecast mean surface temperature C JAN 1990 Drainage of the Caspian and the Aral lake 180 90W 0 90E 180 60N 60N 30N 30N EQ EQ 30S 30S 60S 60S 180 90W 0 90E 180 –50 –40 –30 –20 –10 0 10 20 30 40 50 Figure 12: Global distribution of surface average January temperatures in G2. 158 Acta geographica Slovenica, 54-1, 2014 Forecast mean surface temperature C AUG 1990 Normal lake mask 180 90W 0 90E 180 60N 60N 30N 30N EQ EQ 30S 30S 60S 60S 180 90W 0 90E 180 –50 –40 –30 –20 –10 0 10 20 30 40 50 Figure 13: Global distribution of surface average August air temperatures in G1. Forecast mean surface temperature C AUG 1990 Drainage of the Caspian and the Aral lake 180 90W 0 90E 180 60N 60N 30N 30N EQ EQ 30S 30S 60S 60S 180 90W 0 90E 180 –50 –40 –30 –20 –10 0 10 20 30 40 50 Figure 14: Global distribution of surface average August air temperatures in G2. 159 Modelling of the Aral and Caspian seas drying out influence to climate and environmental changes Dahan A. 2010: Putting the Earth System in a numerical box? The evolution from climate modeling toward global change. Studies in history and philosophy of science B: studies in history and philosophy of modern physics 41-3. DOI: http://dx.doi.org/10.1016/j.shpsb.2010.08.002 Diamond, J. M. 2005: Collapse: how societies choose to fail or succeed. New York. ERA40 reanalyse data 01/01/1989. Atmosphere database. European centre for medium range weather fore- casts (ECMWF). Reading. Gavrilov, M. B. 2005: Poplave i dràva. Vr{a~ke vesti, 23. 5. 2005. Vr{ac. Gavrilov, M. B., Jovanovi}, G. R., Janji}, Z. 2011: Sensitivity of a long-range numerical weather forecast model to small changes of model parameters. Advances in science and research 6. DOI: http://dx.doi.org/ 10.5194/asr-6-13-2011 Goosse, H., Barriat, P. Y., Lefebvre, W., Loutre, M. F., Zunz, V. 2013: Introduction to climate dynamics and climate modeling. Internet: http://www.climate.be/textbook (19. 2. 2013). Hansen, J. E., Sato, M. 2012: Paleoclimate implications for human-made climate change. Climate Change: Inferences from paleoclimate and regional aspects. DOI: http://dx.doi.org/10.1007/978-3-7091-0973-1_2 Hagemann, S., Dümenil, L. 1996: Development of a parameterization of lateral discharge for the global scale. MPI Report 219. Hamburg. Hagemann, S., Dümenil, L. 1998: A parameterization of the lateral waterflow for the global scale. Climate dynamics 14-1. DOI: http://dx.doi.org/10.1007/s003820050205 Hagemann, S., Arpe, K., Roeckner, E. 2006: Evaluation of the hydrological cycle in the ECHAM5 model. Journal of climate 19. DOI: http://dx.doi.org/10.1175/JCLI3831.1 Hagemann, S. 2002: An improved land surface parameter dataset for global and regional climate mod- els. MPI Report 336. Hamburg. Hamon, N., Sepulchere, P., Lefebvre, V., Ramstain, G. 2013: The role of eastern Tethys seaway closure in the Middle Miocene climatic transition (ca. 14 Ma). Climate of the past 9. DOI: http://dx.doi.org/10.5194/ cp-9-2687-2013 Internet 1: http:/ celebrating200years.noaa.gov/breakthroughs/climate_model/AtmosphericModelSchematic.png (19. 2. 2013). Kislov, A., Panin, A., Toropov, P. 2012. Paleostages of the Caspian Sea as a regional benchmark tests for the evaluation of climate model simulations. Climate of the past discussions 8. DOI: http://dx.doi.org/ 10.5194/cpd-8-5053-2012 Micklin, P. 2007. The Aral Sea disaster. annual review of earth and planetary sciences 35. DOI: http:/ dx.doi.org/ 10.1146/annurev.earth.35.031306.140120 Micklin, P., Aladin, N.V. 2008: Reclaiming the Aral Sea. Scientific American 298-4. Internet: http:/ www.sciam.com/ article.cfm?id=reclaiming-the-aral-sea&sc=rss (19. 2. 2013). Murphy, L. N., Kirk-Davidoff, D. B., Mahowald, N., Otto-Bliesner, B. L. 2009: A numerical study of the cli- mate response to lowered Mediterranean Sea level during the Messinian Salinity Crisis. Palaeogeography, palaeoclimatology, palaeoecology 279. DOI: http://dx.doi.org/10.1016/j.palaeo.2009.04.016 Peneva, E. L., Stanev, E. V., Stanychi, S. V., Salokhiddinov, A., Stulina, G. 2004. The recent evolution of the Aral Sea level and water properties: analysis of satellite, gauge and hydrometeorological data. Journal of marine systems 47, 1-4. DOI: http://dx.doi.org/10.1016/j.jmarsys.2003.12.005 Ramstain, G., Fluteau, F., Besse, J., Joussaume, S. 1997: Effect of orogeny, plate motion and land-sea dis- tribution on Eurasian climate change over the past 30 million years. Nature 386. DOI: http://dx.doi.org/ 10.1038/386788a0 Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kirchner, I., Kornblueh, L., Manzini, E., Rhodin, A., Schlese, U., Schulzweida, U., Tompkins, A. 2003: The atmos- pheric general circulation model ECHAM5 – model description 1. Report 349. Hamburg. Roeckner, E., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kornblueh, L., Manzini, E., Schlese, U., Schulzweida, U. 2004: The atmospheric general circulation model ECHAM5, sensitivity of simulated climate to horizontal and vertical resolution 2 II. Report 354. Hamburg. Simmons, A. J., Burridge, D. M., Jarraud, M., Girard, C., Wergen, W. 1989: The ECMWF medium-range prediction models development of the numerical formulations and the impact of increased resolu- tion. Meteorology and atmospheric physics 40, 1-3. DOI: http://dx.doi.org/10.1007/BF01027467 Singh, A., Seitz, F., Schwatke, C. 2012: Inter-annual water storage changes in the Aral Sea from multi-mis- sion satellite altimetry, optical remote sensing, and GRACE satellite gravimetry. Remote sensing of environment 123. DOI: http://dx.doi.org/10.1016/j.rse.2012.01.001 160 Acta geographica Slovenica, 54-1, 2014 Toman, M. J. 2013: Aralsko jezero – simbolj okoljske katastrofe. Proteus 75, 9–10. Tudryn, A., Chalié, F., Lavrushin, Yu. A., Antipov, M. P., Spiridonova, E. A., Lavrushin, V., Tucholka, P., Leroy, S. A. G. 2013: Late Quaternary Caspian Sea environment: Late Khazarian and Early Khvalynian trans- gressions from the lower reaches of the Volga River. Quaternary international 292. DOI: http://dx.doi.org/ 10.1016/j.quaint.2012.10.032 Varuschenko, S. I., Varuschenko, A. N., Klige, R. K. 1987: Changes in the regime of the Caspian Sea and non-terminal water bodies in paleotime. Moscow. Wiin-Nielsen A. 1978: On balance requirements as initial conditions. European centre for medium range weather forecasts (ECMWF) report 9. Berkshire. Vri{er, I. 1953: Padanje gladina Kaspijskega morja. Proteus 15-9. 161 162 Acta geographica Slovenica, 54-1, 2014, 163–178 RISK EDUCATION IN SERBIA Jelena Kova~evi} - Majki}, Marko V. Milo{evi}, Milena Pani}, Dragana Miljanovi}, Jelena ]ali} I]V JEOIVIL MNAVOIL : MN IGSED Logo of the training program for geography teachers »Natural disasters and geography teaching«, one of the rare official activities related to systematic risk education in Serbia. Jelena Kova~evi} - Majki}, Marko V. Milo{evi}, Milena Pani}, Dragana Miljanovi}, Jelena ]ali}, Risk education in Serbia Risk education in Serbia DOI: http://dx.doi.org/10.3986/AGS54305 UDC: 91:504.4(497.11) 504.4:37(497.11) COBISS: 1.01 ABSTRACT: Natural disaster risk reduction can be achieved through vulnerability reduction, as well as through strengthening the resilience of the population. One of the segments leading to these aims is a prop- er risk education. It is the public (compulsory) education system that reaches the greatest number of participants and represents a good platform for the natural disaster knowledge transfer. Geography, as a complex sub- ject that includes both natural and social components, is the most appropriate to transfer the knowledge necessary to improve the resilience. Research done in Serbia (detailed analyses of curricula, textbooks, teachers' role and pupils' knowledge) shows that children do learn about natural disasters but not in a way which provides usable knowledge. KEY WORDS: natural disasters, prevention, education system, geography teaching, knowledge transfer, Serbia The article was submitted for publication on August 31, 2012. ADDRESSES: Jelena Kova~evi} - Majki}, M. Sc. Geographical Institute »Jovan Cviji}« of the Serbian Academy of Sciences and Arts Djure Jak{i}a 9, SRB – 11000 Belgrade, Serbia E-mail: j.kovacevicagi.sanu.ac.rs Marko V. Milo{evi}, M. Sc. Geographical Institute »Jovan Cviji}« of the Serbian Academy of Sciences and Arts Djure Jak{i}a 9, SRB – 11000 Belgrade, Serbia E-mail: m.milosevicagi.sanu.ac.rs Milena Pani}, M. Sc. Geographical Institute »Jovan Cviji}« of the Serbian Academy of Sciences and Arts Djure Jak{i}a 9, SRB – 11000 Belgrade, Serbia E-mail: m.panicagi.sanu.ac.rs Dragana Miljanovi}, M. Sc. Geographical Institute »Jovan Cviji}« of the Serbian Academy of Sciences and Arts Djure Jak{i}a 9, SRB – 11000 Belgrade, Serbia E-mail: d.miljanovicagi.sanu.ac.rs Jelena ]ali}, Ph. D. Geographical Institute »Jovan Cviji}« of the Serbian Academy of Sciences and Arts Djure Jak{i}a 9, SRB – 11000 Belgrade, Serbia E-mail: j.calicagi.sanu.ac.rs 164 Acta geographica Slovenica, 54-1, 2014 1 Introduction According to the majority of relevant references related to the issue of natural disaster risk reduction, var- ious forms of education play an extensive role in this process (e.g. Agenda 21, Hyogo Framework for Action 2005–2015, UN Decade of Education for Sustainable Development 2005–2014, the UN campaigns »Disaster Reduction, Education and Youth« 2000 and »Disaster Risk Reduction Begins at School« 2006–2007, etc.). Education contributes to the realistic risk perceptions, to raising awareness of the possible outcomes, as well as to gaining the necessary knowledge about the proper protective behaviour. It is a platform for building a culture of prevention and disaster-resilient societies. According to Singh (2007), the final out- come of education is » … to enable individuals to become proficient as citizens, having knowledge to make informed decisions that will either help them avoid hazardous situations or enable them to mitigate the effects of a natural disaster …« (Singh 2007, 416). Zorn and Komac (2011, 8) state that prevention is » … key activ- ity in the field of protection against natural disasters.«. Smaller number of casualties and reduced material damage are a proven outcome of prepared and educated societies (Izadkhah and Hosseini 2005). Education about natural disasters leads to risk reduction and fits to the Pressure-and-Release model defined by Wisner et al. (2004). Out of 8 types of vulnerability defined by Aysan (1993, cited in Alcántara-Ayala 2002), three may be substantially reduced through education: educational vulnerability (lack of access to infor- mation and knowledge), attitudinal and motivational vulnerability (lack of public awareness), and cultural vulnerability (related to beliefs and customs). Kuhlicke et al. (2011, 810) define the risk education as a »… pur- poseful transfer of more generalised (thematic, organisational or technical) knowledge on hazards and risks from professionals in teaching institutions to usually (but not necessarily) younger persons within a formalised setting …«. The aim of this paper is to present a detailed analysis of the present level of education related to haz- ards and risk in Serbia. The initial research included the analysis of legislation, school curricula and geography textbooks. In the next steps, the research was extended in the direction of practical aspects – geography teachers' attitudes about inclusion of disaster issues in teaching, as well as evaluation of the present level of knowledge and preparedness of the pupils who experienced a relatively strong earthquake. A particu- lar challenge of the whole research was the fact that the risk education is not included in the formal geography curriculum, so the participants in the process (experts, teachers) are about to find the alternative solu- tions to start the pioneer work in this field in Serbia. 2 Theoretical background In the further text, we use the term »natural disaster« according to the explanation given by the UNIS- DR (2009, 09), which describes the notion of a natural disaster as a »… result of the combination of: the exposure to a hazard; the conditions of vulnerability that are present; and insufficient capacity or measures to reduce or cope with the potential negative consequences …«. 2.1 Why children? There are three main reasons why the children are in the limelight when it comes to hazard and risk edu- cation. The first, as stated by UNISDR (2007) and Ronan et al. (2012), is that the children are the most vulnerable part of a population in case of natural disasters. The second reason, as opposed to the first, is the fact that the children are most liable to change their views and behaviour patterns (Fridl et al. 2009) and at the same time possess considerable strengths, as stated by Peek (2008). The same author reminds that the children's creativity, energy, enthusiasm, and social networks are valuable in the process of risk reduction (Peek 2008), in which children can play an active part (UNISDR 2007). They are now not regard- ed merely as potential victims, but as catalysts for loss reduction (Clerveaux and Spence 2009). The third reason, considered in a longer time span, is that the children are regarded as »tomorrow's leaders« and »key agents for change« (UNICEF and UNISDR 2011), as well as the »powerful forces in behavioural change for the next generation« (Izadkhah and Hosseini 2005). 165 Jelena Kova~evi} - Majki}, Marko V. Milo{evi}, Milena Pani}, Dragana Miljanovi}, Jelena ]ali}, Risk education in Serbia 2.2 Why formal (compulsory) education? In numerous studies and articles formal education is stressed because of its important role in learning on natural disasters (e.g. Wisner 2006; Fridl et al. 2009; Komac et al. 2010; Komac et al. 2011). Without diminishing the importance of informal learning, we insist on the role of formal and compulsory educa- tion, considering the fact that the majority of the population acquire this type of education. The effectiveness of school-based hazard education programs is claimed by many authors (e.g. Ronan et al. 2010; Gulay 2010; Finnis et al. 2010; Johnston et al. 2011). Kuhlicke et al. (2011) highly recommended a combination of a) curriculum based, standardized edu- cation and b) participatory, locally embedded education, which correspond to formal and informal education. Although this is an ideal option, in reality it is sometimes difficult to organize the parallel imple- mentation of both types. In case when the capacities are insufficient to provide the combination of two types of education, it is more efficient to opt for the first type, because the effective risk reduction requires a large proportion of the population who receives the best training possible, while informal education affect small parts of population. 2.3 Why geography? Geographical knowledge, by joining and overlapping of physical (natural) and human (social) elements, is often regarded as a knowledge »for living«, having daily and vocational applications (Gritzner 2004), one of which is certainly the role in prevention of natural disasters. For the same reasons, according to Mitchell (2009), geography is the natural academic »home« for teaching about hazards. As the risk reduction cer- tainly includes the Human-environment relations (HER), the necessary integrative approach is provided through geography as a science (Golledge 2002). Therefore, the position within the risk research is one of geography's greatest strengths (Cross 2009; Stoltman 2006). The same may be applied when discussing the posi- tion of geography as a subject in the system of formal (compulsory) education. The above mentioned references prove that geography is the adequate solution for the inclusion of risk education into the education system. In Serbia, according to official statistics, about 70,000 pupils enroll each year in the 1st grade of prima- ry school, which is compulsory and lasts for eight years (Statistical Survey of Serbia, 2012). Through eight years of primary education, risk education may be gradually included, in accordance with the age, through the subjects »Nature and Society«, »The World Around Us« (1st to 4th grade) and especially »Geography« (5th to 8th grade) (Figure 1). Secondary education is not compulsory, but it is anyway enrolled by about 70,000 students each year (the majority of them finish this level). However, due to its shorter duration and different programs, it cannot be equally efficient in risk education. A small number of the population enrolls higher education (university level) and informal types of education. Although some faculties do cover some natural disaster issues in relatively small parts of their curricula, this level of education has a lesser importance in the overall system of natural disasters pre- vention, due to small coverage. One of the examples in which this small part of population (studying natural disasters at the university level) may be valuable to the system of risk education is, for the beginning, to clear the terminological inconsistencies in the field of natural disasters. Even in expert circles (presenta- tions, articles, and other literature) it often happens that the terminology is used incorrectly and randomly, which reduces the proper wider understanding of processes and interactions. For example, the term »risk« is generally overused, and in majority of cases its use actually refers only to hazard (i.e. does not include vulnerability and resilience). 3 Methods used The actual situation in risk education in Serbia is analyzed at several levels: • analysis of the official legislation structure related to the issue of risk education; • analysis of geography textbooks for primary and secondary schools; • analysis of geography teachers' opinions on the subject; and • analysis of children's reactions, knowledge and attitude after a particular disaster event (M 5.4 earth- quake in the town of Kraljevo). 166 Acta geographica Slovenica, 54-1, 2014 PhD lsooh Msc l sca e r s i t y icg i v 22 n loo U e Bsc thdn 19 a ry 18 yr n a o ilita it 17 dn a Gymnasium Vocational M o c schools c u Craft schools e d S e 15 14 Primary school (higher grades) noit )aycr 10 u o d sl e up Primary school (lower grades) yra momci( 7 rP 6 1 Preschool 1 • subject geography • presence of subjects in which natural disaster themes can be included • subject geography (just some vocations) • the age of the children Figure 1: Educational system in Serbia. 167 Jelena Kova~evi} - Majki}, Marko V. Milo{evi}, Milena Pani}, Dragana Miljanovi}, Jelena ]ali}, Risk education in Serbia Legislation structure analysis is related particularly to legislation within the Serbian educational sys- tem, which directly or indirectly regulates teaching about natural disasters. It includes laws, by-laws, strategies, regulations (rule books), but also the international conventions, which, after a ratification, automatical- ly became parts of Serbian internal legislation. The analysis of geography textbooks for primary and secondary schools was done on a qualitative basis, and included not only the texts, but also the illustrations (charts, sketches, photographs) and thematic maps. The evaluation was done following the three main principles: perception principle, spatial principle and temporal principle. • The perception principle considers various qualifications on particular natural processes, depending on textbook authors and their experiences. It is analyzed whether the particular processes are treated only as natural processes of increased intensity or, on the other hand, they are treated as a natural dis- aster (as defined in the chapter Theoretical background of this paper). If an event is treated only through its genesis and its influences on spatial physiognomy, it has a category of a hazard – a natural process of increased intensity. In cases where an event is treated through its impact on society and its trans- formation, it has a category of a natural disaster. There is also a third case – when the authors point to some positive impacts of natural processes of increased intensity. • The spatial principle stands for the analysis of spatial distribution of natural hazards and disasters stud- ied in textbooks (reactions of children are different for the events in Serbia than for the events abroad). • The temporal principle stands for the analysis of time span between a disaster occurrence and the time when the information about it appears in the textbooks. Analysis of teachers' opinions regarding teaching on natural disasters was done with participation of 361 teachers who attended a specialized training program »Natural disasters and geography teaching«. The research included two steps. The first step was a poll survey using a short questionnaire aimed at estab- lishing whether the teachers are in a position to actually transfer the knowledge they gained at the training program. The close-ended question »Is this program applicable in practice, in schools?« was chosen to determine whether they can include this issue in their classes, regardless of the fact that it is actually not a part of the official curriculum. The offered answers were scaled in 5 options (ordinal-polytomous items), ranging from »I completely agree« to »I completely disagree«. The second phase was an interview aimed at detection of the reasons for the negative answers they gave in the questionnaire. The analysis of children's behaviors, feelings and knowledge in case of a natural disaster, their knowl- edge about natural disaster threats in their living area, and sources of that knowledge, was done through a poll survey in the town of Kraljevo. Kraljevo faced a M 5.4 earthquake on November 3rd 2010 at 1:56 AM and suffered relatively large material damage, with two victims. The poll survey was carried out within a time distance of 16 months after the event. The research included a sample of 300 children: 153 pri- mary school pupils from 5th to 8th grade (aged 11–15) and 147 secondary school students from 1st to 4th grade (aged 15–18). Among the primary school pupils there were more boys (52%), while in secondary schools the number of girls prevailed (60%). All participants have a permanent residence in the town of Kraljevo, 56% of whom live in individual residential facilities. The questionnaire consisted of 17 close-ended questions, five of which were selected for this particular research (activities and feelings during the earth- quake, awareness about the seismic hazard in the area, sources of knowledge about earthquakes, and the type of future training they need). The response scales were nominal-polytomous or dichotomous. The results were processed using the SPSS software. The tests applied include descriptive statistics and non-parametric tests (Pearson chi-square test, binomial test). 4 Results 4.1 Legislation analysis In the Republic of Serbia, the legislation related to risk education is defined by particular education laws, as well as by other laws which do not directly refer to education but mention the education issues in other contexts. Enacting of laws related directly or indirectly to risk education is under the jurisdiction of two ministries: Ministry of Education and Science and Ministry of Interior Affairs. Intersectoral collabora- tion in treating of these issues is generally not synchronized, which results in the lack of desired effects 168 Acta geographica Slovenica, 54-1, 2014 of enacted laws. In other words, up to now, the framework laws have not yet led to enacting of new pro- ficient by-laws in the field of education. Legislation on risk education in Serbia is composed of the following elements (figure 2): International conventions: The Hyogo Framework for Action 2005–2015 has been one of the bases for enacting of the Law on Emergency Situations and the National Strategy on Protection and Rescue in Emergency Situations. Particular laws on education and emergency situations are listed in Tab. 1. The Article 119 of the Law on Emergency Situations foresees that training is done through primary and secondary education, for getting knowledge on the dangers of natural and other disasters, as well as for protection. The Article 4 Paragraph 5 of the Law on the basics of education system states that one of the general aims of the education process is to make children »capable of solving the problems, application of knowl- edge and skills in further education, professional work and everyday life«, which completely corresponds to the need for risk education. The Laws on primary and secondary schools (Articles 20 and 24, respectively), declare that the curriculum is enacted by the Minister of education, according to the suggestion of the advisers for particular subjects. Table 1: Laws in the Republic of Serbia related to education and risk management Law Official gazette number Law on Emergency Situations 111/09 Law on the Basics of Education System 72/2009, 52/2011 Law on Primary Schools 50/92, 53/93, 67/93, 48/94, 66/94, 22/02, 62/03, 64/03, 101/05, 72/09 Law on Secondary Schools 50/92, 53/93, 67/93, 48/94, 24/96, 23/02, 25/02, 62/03, 64/03, 101/05, 72/09 Strategies: The National Strategy on Protection and Rescue in Emergency Situations (2011) says with- in the Strategic section 3 that »issues related to protection, rescue and disaster risk reduction should be incorporated into the curricula of all educational institutions«. Curricula are defined in the Regulations enacted by the Ministry of Education (table 2). The analyzed regulations for the primary school curricula show that there is only one lesson related to some kind of natural disasters: »Volcanism and earthquakes« in the 5th grade. There are two kinds of secondary schools, with different curricula: gymnasium and vocational schools. In the 1st grade of gymnasium, there are three lessons partially related to natural disasters: Volcanism; Earthquakes (with seismically active zones in Serbia); and Precipitation. In other gymnasium grades there are no geographical lessons treating the issue of nat- ural disasters. Among the vocational schools, only in the 2nd grade of touristic vocational school, there are two geography lessons related to natural disasters: Water-management problems in Serbia; and Natural disasters. The fact that Curricula are a bottleneck not properly transferring the legislation-provided pos- sibilities towards the schools is one of the important conclusions we have reached in this study. Table 2: Regulations on the school curricula in the Republic of Serbia Regulations Slùbeni glasnik (Official gazette – Educational gazette) number Regulation on the Plan for the 2nd cycle of primary education 6/2007, 2/2010, 7/2010, 3/2011 and the Curriculum for 5th grade of primary education Regulations on the Curricula for 6th, 7th and 8th grade 5/08, 6/09, 2/2010 of primary education Regulation on the Plan for the gymnasium education 110-00-32/97-01 and the Curriculum for 1st grade of gymnasium Regulation on the Curriculum for 2nd, 3rd and 4th grade 11/2006 of gymnasium 4.2 Geography textbooks evaluation The perception principle: The above-mentioned Curricula directed the contents of geography textbooks. Within this research, 23 geography textbooks were analysed, all of which are formally approved by the Ministry 169 Jelena Kova~evi} - Majki}, Marko V. Milo{evi}, Milena Pani}, Dragana Miljanovi}, Jelena ]ali}, Risk education in Serbia INTERNATIONAL C ONVENTIONS L AWS ON EDUCATION AND EMERGANCY SITUATIONS CURRICUL A GEO GRAPHY TEACHING Figure 2: Legal framework for the establishment of Risk education in Serbia. The Curricula are a bottleneck not properly transferring the legislation-provided possibilities towards the schools. of Education for usage in schools. Greater variety of textbooks is characteristic for the primary school, especially 5th grade (six different textbooks), while secondary school programs mostly have one available textbook per grade. The lessons precisely defined by the curricula occur regularly in all textbooks, regardless of the pub- lisher and the edition. Additional contents and aspects related to natural disasters occur randomly, depending on the authors of the textbooks. Unfortunately, the processes which are systematically studied in all text- books are presented as hazards (natural processes) and not as natural disasters. Geography textbooks mention the following natural processes which may have the characteristic of a disaster: meteorites, earthquakes, volcanoes, tsunamis, landslides, avalanches, floods, tropical cyclones, tornadoes, hail (table 3). Only sev- eral authors mention these processes in the context of natural disasters. The example of the lesson Earthquakes (5th grade) shows that its main function is to explain the functioning of plate tectonics, which is common for all 5th grade textbooks. Only in two editions the lesson includes a short instruction on how to properly behave during an earthquake (Sitarica and Tadi} 2010, Milivojevi} and ]ali} 2012). In the lessons in human and regional geography, natural disasters are occasionally mentioned in a pos- itive context. The most typical examples are the floods in the valleys of the Nile River and the Tigris-Euphrates River system, or the volcanic activity in Indonesia, which in longer time spans lead to formation of natural resources, such as high quality soils or ores (e.g. Jakovljevi} and Birovljev 2012; \uri} 2011) (Figure 3). The lessons on Egypt mention the Nile floods mostly as a process which enabled the formation and devel- opment of the whole country, while only few authors point also to the negative consequences of the Nile floods (Sitarica and Tadi} 2010). The spatial and temporal principles: The analysis of geography textbooks showed that the majority of the described examples of hazaZrds and disasters are situated out of Serbia – either in European or, even more often, non-European countries. The most obvious examples are earthquakes: many Serbian text- books describe the M 9.1 earthquake in the Indian Ocean in 2004, while none mentions multiple M 5 events 170 Acta geographica Slovenica, 54-1, 2014 IV / / / / / / / / / / / / / ) l s a n e n d tioa / / / / / / / / / / / / / ra tioa c c u (g o d n v e tio III ac - u a m d nm iu / ▲ / / ▲ / / ▲ / ▲ ▲ / / l e y s a g n tioa l c a n o n tioa r v tio / / / / / a c ▼ ▲ ▲ ▼ ▲ ▲ ▼ ▼ o c ud m ov e ius II a - n a m n m / / / / / / / / / / y m iu ● ▲ ▲ g y s g l –oo l h a n c n tio s tio a / / / / / / / / / / / / / ry a c a c u d o d n v e o I ceS -an m m iu ▼ ▼ ▲ ▼ ▼ ▲ ▲ / ▲ ▲ ▲ ▼ ▲ y s g III / / / / / / / / / V ▲ ▼ ▲ ▲ )sedra II ● ● V / ▲ / ▲ ▲ / / ▲ / / . ▲ ▼ s l (g k o o o o hc tbx sry te a I / / / / / / / / y V ▲ ▲ ▼ ▼ hp rim ra P goe gn V / / / / / / / ia ▲ ▼ ▲ ▲ ▲ ▲ rbe t)x Se tee th s s re th in e ) s s tu s in e s e se u e n ra c ils s c e lo p ro tae is ro c s m d s ek p y e l p de te a te rm o i e o l c hc e t ra e la rite u p a h to o q n m d s a a lo n m g fire tu n a ic d la u a t (s r re te o e rth lc u p il-s x ills rn a tre ro a ild (n te a o lo v x te s M E V Ts H To Tro F A E D H W rd n a o is zaa c r e l d in f h te ra itiv rig s l o a s tu e o a l o v is p f n l d a tria rs le o s rs e ra in w rs tes rs tes t th tu rd ie rre te a te a ll s a a rv te s is a is n za t a e a ly a a v r tra is a x is l d n s a l d h d o te l d a o a a e sa f e l d ic a ic d d g ie h a g d is o ic g ie ie lo ic d d tin tu : T s g lo l d rs y : a tu tu 3 ro lo to d t s ra te h o a n s s o le sa p ro e tre b tu o te d – – – n a is e e y lim ge Ta N D G M H C L ▲ ▼ ● / – 171 Jelena Kova~evi} - Majki}, Marko V. Milo{evi}, Milena Pani}, Dragana Miljanovi}, Jelena ]ali}, Risk education in Serbia in Serbia, which in fact have much greater impact on the real everyday situations. The reason for this para- dox lies within the fact that textbooks tend to show the most intensive event of a kind, and these are almost never related to Serbia. In terms of spatial aspect, in some European countries there is the opposite case, meaning that content of geography textbooks is primarily related to their own countries (Senega~nik 2010). On the other hand, in Serbia, the fact that the 2004 Indian Ocean earthquake has its place in many text- books shows a good temporal accordance between an event and the time of textbook response. The greatest natural disasters in Serbia in the period 2000–2011 were: the floods of the Tami{ River in 2005, numerous landslides (e.g. Bogdanje) in the spring of 2006, extreme air temperatures (44.9 °C in Smederevska Palanka) in 2007, and the Kraljevo earthquake (M 5.4) in 2010. Although these disasters of Atmosphere Hidros ical Cultural Social Politi p c h a e l re Lithosphere Biosphere Econom Natural Hazards Societies NATURAL DISASTERS Time span Natural resources Figure 3: Sketch of the natural disaster system, with three levels at which the issue is treated in Serbian geography textbooks (▲ – hazard, ▼ – disaster, ● – resource; as in Table 3). 172 Acta geographica Slovenica, 54-1, 2014 regional scale had the human victims, large evacuations and extensive material damage, none of them has been mentioned in geography textbooks up to now – neither in the lessons on natural processes, nor in the lessons covering the regions of the affected areas. We can conclude that there is neither temporal nor spatial coordination between the Serbian natural disasters and Serbian geography textbooks. This fact leads to the substantial decrease of awareness and preparedness for a potential event. 4.3 Teachers' opinion The analysis of teachers' opinions shows that a large number (80%) of teachers believe their new knowl- edge could be applied in the classroom (Figure 4). A small number of teachers mostly agrees that they can apply the new knowledge (14%), while a small number of them partially agree (5%). Very few teachers believe that the theme of natural disasters would not be useful for their future work. Since the positive opinion on the applicability of new knowledge gained at the training program highly dominates, it can be interpreted as their will to teach about an attractive and important matter. In the interview with the teachers, we discussed the reasons why some of them are anxious that the new knowledge on natural disasters is not sufficiently useful for their future work. The limitations they stat- ed can be categorized into three groups: • Formal limitations: extensive geography curriculum, but small number of classes per week, and no lessons on natural disasters. Solution of these problems requires a systematic approach, which means slow procedure. Therefore, the intermediate solution should be searched even prior to the modification of the curriculum (cf. Cummins 2010). Authors of textbooks should include innovations of this kind in textbooks, and publishers should support it. In Serbia, these changes occur slowly and there are rare exam- ples of the positive outcomes of such initiatives (Milivojevi} and ]ali} 2012; Sitarica and Tadi} 2010). Additional limitation in the implementation of these changes, as pointed by Gr~i} (2001), is the shaken position of geography in the system of sciences, which led to its suppression and destabilization in schools. This situation is caused by inaccordance between the curricula and pupils' perception, by excessive descrip- tive contents, by gaps in education and training of geography teachers, and the gap between university professors and teachers at schools (»university geography« vs. »school geography«) (Gr~i} 2001). Therefore, it is more difficult to impose the importance of geography as a science that teaches practical things in life. 1% 5% 0% Program is applicable in practice, in schools 14% Completely Agree Mostly Agree Partial y Agree Mostly Disagree 80% Completely Disagree Figure 4: Applicability of additional knowledge about natural hazards in geography teaching, based on poll survey results (361 teachers). 173 Jelena Kova~evi} - Majki}, Marko V. Milo{evi}, Milena Pani}, Dragana Miljanovi}, Jelena ]ali}, Risk education in Serbia • Pupils' motivation: the degree of their interest to learn is often reported to be low (correlation with age, gender, discipline in class, the teacher, the methods used in class). This could be overcome by the fact that the issue of natural disasters is usually attractive to children and offers the possibilities for creative work (Mitchell et al. 2008; Reinfried 2004). • Teachers' motivation – the degree of their interest to use their right to be innovative in teaching. Many teachers are strictly adhering to the curriculum, and as a reason for not introducing innovations in teach- ing they even state a fear of rigorous control inspections if they depart from the curriculum. This practice urgently needs a substantial change. On the other hand, there are also teachers who notice the lack of information in textbooks and atlases (e.g. Simovi}, 2007). According to Mitchell et al. (2008, 171), »… answering why we teach hazards is fairly straightforward, and more pressing question at present is this: how should we teach about hazards …?«. Due to the marginal position of geography in education in Serbia (Gr~i} 2001) it is often difficult for some teachers to regain their lost self-confidence. The geographic scientific community should remind them that the future of geography lies in the »… interdisciplinary themes, (…) global processes, environmental problems, natural disasters, demographic changes, uneven region- al development …« (Gr~i} 2001) and that they need just to redesign their knowledge (Annan 2006), understanding and accepting the new important role of geography. Generally speaking about the role of a teacher, Fridl et al (2009) note that their important role is to broaden their students' horizons by presenting and addressing a number of already existing and new topics differently. 4.4 Children's selfreported behaviors, feelings and knowledge The poll survey about children's behaviors, feelings and knowledge on natural disasters, carried out in Kraljevo, showed some worrying results. When asked about their reaction during the earthquake, 59% of the total group responded that they stayed in their homes not taking any measures of protection, while 24% said that they » just ran out.« Only 15% of participants reacted correctly, looking for an adequate shelter (under a table or within a door frame). The three mentioned answers are almost equally represented among pupils in primary and sec- ondary schools. About 14% said that they reacted some other way (e.g. that they slept over mentioned event), which was a characteristic response for secondary schools (within this group, 73% are secondary schools students). More detailed analysis of primary schools student reactions during the Kraljevo earth- quake was done by Pani} et al. (2013). When asked about their feelings at the time of the event, approximately 35% declared that they were frightened, whereas the feeling of complete helplessness expressed through » I was completely frightened and I did not know what to do,« was the answer of 20% of children. Among those who felt helpless, there were more girls (77%) compared to boys (23%). About 26% of the participants stayed calm during the earth- quake, without any panic feeling, which is more common for the boys (62%) than for the girls (38%). About 18% did not choose any of the following categories (or they slept through the earthquake). As for the question » Where did you learn how to behave during an earthquake to protect yourself from harm? «, 26% said that they listened to their parents and the advice received from them. This response was more common for girls (67%) and secondary school pupils (63%). About 25% of respondents singled out the school as the place where they learned something about behavior during the earthquake, which was more common for secondary school pupils (55%). The answer »mass media« was singled out by 21% of participants, and the internet by 9%. About 5% of participants were using some other sources, while 12% said they never heard of such information. Extremly large number of pupils (77%) was not aware that they live in the area threatened by seis- mic hazard. A smaller group (23%) are those who were aware of the earthquake occurrence possibility, 56% of which in primary and 44% in secondary schools. When asked about the presence of earthquake-related issues in geography textbooks, 33% said they thought that the present contents were enough, while 67% thought that the existing material » should be expanded with the instructions on how to behave during an earthquake.« This attitude is equally character- istic for primary and secondary school pupils, with the exception that 100% of students in the final year of secondary school gave this response. Analyzing the poll survey results in total, it is conspicuous that over 70% of children (regardless of age) did not respond adequately at the time of the earthquake. Since at that time (01:56 AM) children 174 Acta geographica Slovenica, 54-1, 2014 were mostly in their homes, we can suspect that they largely relied on the advice and guidance of their parents. Thus, the results show that neither parents nor children reacted reasonably and correctly, due to the lack of basic knowledge and skills to cope with emergency situations. Taking this into account, it is not surprising that more than 50% were extremely frightened or they panicked. As the earthquake prevention and protection measures are not developed in Serbia, and are not includ- ed in geography curriculum or textbooks, the poll showed that the parents are the most important source of information for children. However, in the days following the earthquake, a great number of aftershocks occurred. In this peri- od, the additional lessons dedicated to earthquakes were organized in Kraljevo schools (regardless of geography classes). There were also a lot of information spread through the media, and individuals searched for information themselves on the Internet. Therefore, the pupils realized that their previous knowledge was highly insufficient, which made them believe that it is necessary to expand the existing curriculum and include mentioned topics to the geography textbooks, together with the practical training. Apart from the lack of general information, there is also a considerable lack of the knowledge about the local envi- ronment. A dramatically large number of children were unaware that their hometown and its wider area are facing a relatively high seismic hazard. 5 Conclusion In the process of prevention of natural disasters, it is important to strengthen the awareness of teachers and children they are a very important link in the transmission of information. One of the basic princi- ples of the Hyogo Framework is a better exchange and access to information, which is very successfully enforced through the International Decade for Natural Disaster Reduction (IDNDR) 1990–2009, and is still carried out through the Building the Resilience of Nations and Communities to Disaster 2005–2015. As a good information exchange is an important condition for preparedness and readiness for action in the event of natural disasters, all the links in information transmission have an equal importance. The exam- ple in Fig. 5 shows the geographers (experts, teachers) and pupils as the important links in the process of information exchange. Following the Chain of information exchange, children should have an equal role as adults. Considering our poll survey results they are aware that they do not want to be victims, but active participants (as already described in numerous references, e.g. Clerveaux and Spence 2009; Chen et al. 2013). The efficiency of such approach was comfirmed by the positive experience of school-based earthquake education in Iran (Parsizadeh and Ghafory-Ashtiany 2010). In Serbia, presently we only have a partial hazard education, but still not a proper risk education. The cov- erage of hazards is systematic, while the coverage of risk is random and poorly represented. General legal capacities for the inclusion of risk education (which would be an upgrade of the present hazard educa- tion) do exist, but presently the lower range legislation (Regulations on Curricula) lags behind and fails to follow the recommendations of the international conventions and national laws. Regardless of the pre- sent flaws in the curricula, the formal (compulsory) education and geography teaching are the best framework for risk education. The possible solutions do require the changes of curricula, but before the new regula- tions are enacted, the teachers' interventions in the teaching process must compensate the present limitations. Expert Training Geography programs, Parents, teaching, Informal in the field of Geography Pupil any member of scientific articles, textbooks conversation natural disasters teacher monographs local community I n s t i t u t i o n a l Non-institutional Figure 5: The chain of information exchange in the education process. 175 Jelena Kova~evi} - Majki}, Marko V. Milo{evi}, Milena Pani}, Dragana Miljanovi}, Jelena ]ali}, Risk education in Serbia 6 Acknowledgement The paper is a result of the project funded by Ministry of Education, Science and Technological Development, Republic of Serbia (project no. 47007). We are grateful to all teachers and pupils from Kraljevo schools who participated in the pool survey. 7 References Agenda 21. Internet: http://www.un.org/esa/sustdev/documents/english/Agenda21.pdf (27. 7. 2012) Alcántara-Ayala, I. 2002: Geomorphology, natural hazards, vulnerability and prevention of natural disasters in developing countries. Geomorphology 47-2. DOI: http://dx.doi.org/10.1016/S0169-555X(02)00083-1 Annan, K. 2006: Funkcija geografije po mi{ljenju Ujedinjenih Nacija. Globus 31. Chen, C. Y., Yu, K. H., Chen, M. Y. 2012. Planning of professional teacher-training program for disaster prevention education and executing efficiency evaluation. Disaster prevention and management 21-5. DOI: http://dx.doi.org/10.1108/09653561211278734 Clerveaux, V., Spence, B. 2009: The communication of disaster information and knowledge to children using game technique: The disaster awareness game. International journal of environmental research 3-2. Cross, J. A. 2009: Teaching hazards by geographers: A decade of change. Environmental Hazards 8. DOI: http://dx.doi.org/10.3763/ehaz.2009.0002 Cummnis, M. 2010: Eleven Years On: A case study of geography practices and perspectives within an Irish primary dchool. Internet: http://www.teachingcouncil.ie/_fileupload/Research/Bursary%20Summaries/ MCummins_WEB.pdf (13. 8. 2012). \uri}, V. 2011: Geografija za II razred gimnazije. Beograd. Finnis, K.K., Johnston, D.M., Ronan, K.R., White, J.D. 2010: Hazard perceptions and preparedness of Taranaki youth. Disaster prevention and management 19-2. DOI: http://dx.doi.org/10.1108/09653561011037986 Golledge, R. G. 2002: The nature of geographic knowledge. Annals of the Association of American geo- graphers 92-1. DOI: http://dx.doi.org/10.1111/1467-8306.00276 Gr~i}, M. 2001: Teorijsko-metodolo{ki problemi geografije. Globus 26. Beograd. Gritzner, C. F. 2004: The geographic »mental map«: Can »anyone« (really) teach geography? Journal of geography 103-1. DOI: http://dx.doi.org/10.1080/00221340408978571 Gulay, H. 2010: An earthquake education program with parent participation for preschool children. Educational research and review 5-10. Fridl, J., Urbanc, M., Pipan, P. 2009: The importance of teachers' perception of space in education. Acta geographica Slovenica, 49-2. DOI: http://dx.doi.org/10.3986/AGS49205 Hyogo Framework for Action 2005–2015: Building the resilience of nations and communities to disas- ters: 2005. Internet: http://www.unisdr.org/files/1037_hyogoframeworkforactionenglish.pdf (27. 7. 2012). Izadkhah, Y. O., Hosseini, M. 2005: Towards resilient communities in developing countries through edu- cation of children for disaster preparedness. International Journal of Emergency Management 2-3, Geneva. DOI: http://dx.doi.org/10.1504/IJEM.2005.007355 Jakovljevi}, J., Birovljev, N. 2009: Moja planeta 7. Beograd Johnston, D., Tarrant, R., Tipler, K., Coomer, M., Pedersen, S., Garside, R. 2011: Preparing schools for future earthquakes in New Zealand: lessons form an evaluation of a Wellington school exercise. The Australian Journal of Emergency Management 26-1. Komac, B., Cigli~, R., Erharti~, B., Ga{peri~, P., Kozina, J., Oroèn Adami~, M., Pav{ek, M., Pipan, P., Volk, M., Zorn, M. 2010: Risk Education and Natural Hazards. CapHaz-Net WP6 Report. Anton-Melik geo- graphical institute of the Scientific research centre of the Slovenian academy of sciences and arts. Ljubljana. Internet: http://caphaz-net.org/outcomes-results/CapHaz-Net_WP6_Risk-Education (25. 8. 2012). Komac, B., Zorn, M., Cigli~, R. 2011: Izobraèvanje o naravnih nesre~ah v Evropi. Ljubljana. Internet: http://zalozba.zrc-sazu.si/414 Kuhlicke, C., Steinführer, A., Begg, C., Bianchizza C., Bründl, M., Buchecker, M., De Marchi, B., Di Masso Tarditti M., Höppner, C., Komac, B., Lemkow, L., Luther, J., McCarthy, S., Pellizzoni, L., Renn, O., Scolobig, 176 Acta geographica Slovenica, 54-1, 2014 A., Supramaniam, M., Tapsell, S., Wachinger, G., Walker, G., Whittle, R., Zorn, M., Faulkner, H. 2011: Perspectives on social capacity building for natural hazards: outlining an emerging field of research and practice in Europe. Environmental science & policy 14. DOI: http://dx.doi.org/10.1016/j.envs- ci.2011.05.001 Milivojevi}, M., ]ali}, J. 2012: Geografija 5, za 5. razred osnovne {kole. Beograd. Mitchell, J. T., Borden, K. A., Schmidtlein, M. C. 2008: Teaching Hazards Geography and Geographic Information Systems: A Middle School Level Experience. International research in geographical and environmental education 17-2. DOI: http://dx.doi.org/10.1080/10382040802148679 Mitchell J. T. 2009: Hazards education and academic standards in the Southeast United States, International Research in Geographical and Environmental Education 18-2. Colchester. DOI: http://dx.doi.org/10.1080/ 10382040902861221 Pani}, M., Kova~evi} - Majki}, J., Miljanovi}, D., Mileti}, R. 2013: Importance of natural disaster educa- tion – Case study of the earthquake near the city of Kraljevo – first results. Journal of the Geographical Institute »Jovan Cviji}« SASA, 63(1). DOI: http://dx.doi.org/10.2298/IJGI121121001P Parsizadeh, F., Ghafory-Ashtiany M. 2010: Iran public education and awareness program and its achieve- ments. Disaster Prevention and Management 19-1. Bredford. DOI: http://dx.doi.org/10.1108/ 09653561011022126 Peek, L. 2008: Children and Disasters: Understanding Vulnerability, Developing Capacities, and Promoting Resilience – An Introduction Children. Youth, and Environments 18-1. Reinfried, S. 2004: Do Curriculum Reforms Affect Classroom Teaching in Geography? The Case Study of Switzerland. International Research in Geographical and Environmental Education 13-3. DOI: http://dx.doi.org/10.1080/10382040408668518 Ronan, K. R., Crellin, K., Johnston, D. 2010: Correlates of hazards education for youth: a replication study. Natural Hazards 53. DOI: http://dx.doi.org/10.1007/s11069-009-9444-6 Ronan, K. R., Crellin, K., Johnston, D. M. 2012: Community readiness for a new tsunami warning system: quasi-experimental and benchmarking evaluation of a school education component. Natural Hazards 61. DOI: http://dx.doi.org/10.1007/s11069-011-0070-8 Senega~nik, J. 2010: The extent and content of the presentation of the geography of Europe in school text- books in European countries. Acta geographica Slovenica 50-1. DOI: http:/ dx.doi.org/10.3986/AGS50104 Singh, R.B 2007: Current Curriculum Initiatives and Perspectives in Education for Natural Disaster Reduction in India. International Perspectives on Natural Disasters: Occurence, Mitigation, and Consequences. Dordrecht. Simovi}, Z. @. 2007: Primena geografskih atlasa i karata u nastavi geografije (Ta~nost sadràja na karta- ma kao jedan od uslova pravilnog formiranja geografskog mi{ljenja kod u~enika). Collection of papers 57. Geographical Institute »Jovan Cvijic« Serbian Academy of Sciences and Arts. Belgrade. Internet: http:/ www.gi.sanu.ac.rs/rs/izdanja/zbornik/pdf/057/gijc_zr_57_054_z_simovic_srp_eng.pdf (4. 9. 2012). Sitarica, R., Tadi}, M. 2010: Geografija za 5. razred osnovne {kole. Beograd. Statistical Office of the Republic of Serbia 2012: Pupils of primary school in the Republic of Serbia Beginning of 2011/2012. Belgrade. Internet: http:/ webrzs.stat.gov.rs/WebSite/Public/ReportResultView.aspx?rptKey=ind (5. 8. 2012). Stoltman, J. P. 2006: Turning points in geographic education. Geographical Education in a Changing World: Past Experience, Current Trends and Future Challenges. Dordrecht. The National Strategy on Protection and Rescue in Emergency Situations: 2011. National Assembly of the Republic of Serbia. Belgrade. UN Decade of Education for Sustainable Development 2005-2014. Internet: http:/ www.desd.org (21. 8. 2012). UNICEF and UNISDR 2011: Children and disasters: building resilience through education. Internet: http://www.unisdr.org/files/24583_childrenanddisastersbuildingresilie.pdf (27. 7. 2012). UNISDR 2007: Towards a culture of prevention: disaster risk reduction begins at school – good practices and lessons learned. Geneva. Internet: http://www.unisdr.org/files/761_education-good-practices.pdf (25. 7. 2012) UNISDR 2009: Terminology on Disaster Risk Reduction. http:/ www.unisdr.org/files/7817_UNISDRTerminology- English.pdf (5. 8. 2012) UNISDR World Campaign – disaster risk reduction begins at school 2006–2007 Internet: http:/ www.unisdr.org/ 2007/campaign/wdrc-2006-2007.htm (1. 8. 2012) 177 Jelena Kova~evi} - Majki}, Marko V. Milo{evi}, Milena Pani}, Dragana Miljanovi}, Jelena ]ali}, Risk education in Serbia UN World Disaster Reduction Campaign on Disaster Prevention, Education and Youth: 2000. Internet: http://www.unisdr.org/2000/campaign/pa-camp00-kit-eng.htm (8. 8. 2012) Wisner, B., Blaikie, P., Cannon, T., Davis, I. 2004: At risk: natural hazards, people's vulnerability and disasters. London and New York. Wisner, B. 2006: Let Our Children Teach Us!. A Review of the Role of Education and Knowledge in Disaster Risk Reduction. Internet// www.unisdr.org/knowlwdge-education (15. 7. 2012) Zorn, M., Komac, B. 2011: Damage caused by natural disasters in Slovenia and globally between 1995 and 2010. Acta geographica Slovenica letnik 51-1. DOI: http://dx.doi.org/10.3986/AGS51101 178 Acta geographica Slovenica, 54-1, 2014, 179–188 THE PHYLOSOPHY AND APPLICABILITY OF ECOREMEDIATIONS FOR THE PROTECTION OF WATER ECOSYSTEMS Zorica Svir~ev, Svetislav Krsti}, Tamara Vaì} VE^IRV SAICROZ Ecoremediation – following nature. Zorica Svir~ev, Svetislav Krsti}, Tamara Vaì}, The phylosophy and applicability of ecoremediations for the protection of water ecosystems The phylosophy and applicability of ecoremediations for the protection of water ecosystems DOI: http://dx.doi.org/10.3986/AGS54306 UDC: 574.5:556.11 COBISS: 1.01 ABSTRACT: The problem of accelerated eutrophication of the water ecosystems has not been appreci- ated proportionally to the development of human society today. Accelerated or fast eutrophication is detected destiny in majority of ecosystems today, mainly due to adverse human impact. This paper aims to intro- duce ERM methods in treating the problems arising from increased total capacity and saprobity and also accelerated eutrophication. In this way the broadness and importance of ERM as an ecosystem service for the water protection should be emphasized. The basic characteristics of ERM are its high buffer and self-protective capacities, and preservation of natural habitats and biological diversity. ERM represents the šre- turning to nature’ approach aiming to preserve or re-establish the natural balance of the ecosystems, but also a human endeavor that enables new jobs and by-side activities important for economic and social devel- opment of the human society. KEY WORDS: ecoremediation, eutrophication, water quality, algal blooms, sustainable development The article was submitted for publication on December 14, 2012. ADDRESSES: Zorica Svir~ev, Ph. D. University of Novi Sad Faculty of Sciences, Department of Biology and Ecology Trg Dositeja Obradovica 2, Novi Sad, Serbia E-mail: izlecenjeayahoo.com Svetislav Krsti}, Ph. D. Institute of Biology, Faculty of Natural Sciences Arhimedova 5, Skopje, Macedonia E-mail: svetakrsticayahoo.com Tamara Vaì}, M. Sc. University of Novi Sad Faculty of Sciences, Department of Biology and Ecology Trg Dositeja Obradovica 2, Novi Sad, Serbia E-mail: tamara.vazicagmail.com 180 Acta geographica Slovenica, 54-1, 2014 1 Introduction Humanity has emerged as a major force in the operation of the biosphere, with a significant imprint on the Earth System, challenging social–ecological resilience. This new situation calls for a fundamental shift in perspectives, world views, and institutions. Human development and progress must be reconnected to the capacity of the biosphere and essential ecosystem services to be sustained (Folke at al. 2011). The issue at stake is broader than climate change. It is about a whole spectrum of global environmental changes that interplay with interdependent and rapidly globalizing human societies. A key challenge for human- ity in this new situation is to understand its role in the Earth System, start accounting for and governing natural capital and actively shape development in tune with the biosphere (Rockström et al. 2009). This is a new situation and it calls for new perspectives and paradigms on human development and progress-recon- necting to the biosphere and becoming active stewards of the Earth System as a whole. Water ecosystems in this regard are particularly vulnerable. Immense pressures resulting from abstrac- tions of surface and ground waters, input of numerous polluters in vast quantities and the global climate change processes have caused accelerated eutrophication and subsequent pollution of many ecosystems. It is therefore an urgent imperative to shift the historical view on waters as a resource towards their role as a life supporting systems, or the bloodstreams of the biosphere, with people as embedded part (Hoff 2009). Indeed, the new approaches linking water and ecosystem services, like adaptive water governance, are already emerging (Pahl-Wostl et al. 2011). The knowledge on the use of ecoremediation (ERM) methods for wastewater treatment spread quite slowly during the 1970s and the early 1980s both in Europe and North America. The development of ecosys- tem methods has been taking place separately and inconsistently (Griesseler Bulc and Slak 2009). There are currently thousands of constructed wetlands throughout the world, but the use of these systems for treating wastewater is a relatively new technology in most countries (Vovk Korè and Vrhov{ek 2006). VE^IRV SAICROZ Figure 1: A constructed wetland for a domestic waste water treatement, Slovenia. 181 Zorica Svir~ev, Svetislav Krsti}, Tamara Vaì}, The phylosophy and applicability of ecoremediations for the protection of water ecosystems Thirty years of the research on the use of constructed wetlands as the most common ERM method for various types of wastewater (Brix 1994; Scholz et al. 2007a) has proven that the great number of early worries and negative arguments has been successfully denied. For example, it has been shown that con- structed wetlands may perform well under cold climatic conditions (Mander and Jenssen 2003). Also, constructed wetlands are commonly used in countries with high population densities, such as Denmark, Belgium or the Netherlands, while the U.S. government encourages the use of simple wetlands for eco- nomical treatment of sewage from small communities of less than 5000 people (Horne 2005). The use of constructed wetlands for various industrial effluents is also becoming quite common. Ecoremediation method in broader sense is applied by Vrhov{ek (Vovk Korè and Vrhov{ek 2006) more than 20 years in the countries of ex Yugoslavia. The efficiency and genuinity of this idea has forced us in a more scientific, but also phylosophical approach which, we hope, will speed-up the practical imple- mentation of ERM (Fig 1). 2 Ecoremediation – the philosophical approach Ecoremediation as a system for protection, sanation and remediation of the environment can be appre- ciated from very different stand points. Globaly it can be said that ERM is a buffer system that enables the re-establishing of the disturbed ecological balance in its natural position. As an immune system of our planet, ERM is the preventive defence that protects against the system being in a not desirable mod- ified stage. In general, ERM is consist of abiotic and biotic elements and processes that have a role in balancing the ecosystems. Where is the recognition of ERM as a system for protection, sanation and remediation of the envi- ronment coming from? How was the ERM as a principle of human endevour recognised? In millions of years, the nature and ecosystems evolved exceptional defensive and self-protective capac- ity to safeguard themselves against sudden and powerful impacts and to remove their harmful consequences. VE^IRV SAICROZ Figure 2: A natural wetland – reed belt along river and channels in Vojvodina, Serbia. 182 Acta geographica Slovenica, 54-1, 2014 Through its history, the nature has experienced many catastrophes and survived them for this reason. Aquatic ecosystems and wetlands have a high retention capacity and could prevent flooding as well as severe and specific physical, chemical and toxic pollution. These ecosystems neutralize toxins and efficiently reduce various pathogenic organisms. Moreover, they increase biodiversity and contribute to many so far unknown or hardly known processes maintaining the equilibrium on our planet. Ecoremediation comprises sys- tems and processes which function in natural and artificial ecosystems; it protects and restores the environment. It is comparatively inexpensive and highly efficient in protection of water resources, streams, rivers, lakes, groundwater and the sea. The basic characteristics of ERM, which can be utilized and improved, are its high buffer and self-protective capacities, and preservation of natural habitats and biological diversity (Vovk Korè and Vrhov{ek 2006). By observing the different ecosystem's ability for šself reparation’ after natural or anthropogenic impacts, the ERM system was recognized. Over the question How has a certain ecosystem »learned« to survive and re-establish the functional relationships, the basic ERM field is discovered. And, due to the complexity of ecosystems' properties, the term ERM system is used rather than ERM methods. ERM principles are the con- stitutional part of ecosystems' functioning since the begining of life on our planet. In the time scale of these global processes man is nothing but a tiny part. Nevertheless, on the scale of the impact on planet Earth, man is a very important and detrimental element (Rockström etal. 2009). Our attitude towards the plan- et has become a question of its survival. In this constalation, ERM becomes a survival phylosophy. Natural selection of new solutions for ecosystem balance maintenance unequivocally leads us to ERM concept which incorporates: research, new technology development and education that together represent the new philosophical approach in line with the global paradigm of sustainable development. 3 The link between ecoremediation and eutrophication The fact that biologists have often neglected the importance of abiotic factors has contributed to insuf- ficient appreciation of the terms oligotrophy and eutrophy of the water systems. Dividing of water ecosystems to oligo and eu trophic ones is a separation to long and short living. Overall ecosystem elements that deter- mine and define the organic matter quantity in the water are termed the total capacity of that water ecosystem. The total capacity is a whole chain of parameters whose combination (in a form of specific physic-chem- ical set-up) will guide the course of the eutrophication. Very specific elements which are part of, or influence the biomass synthesis in water ecosystems are essential for the primary production. Disproportion or lack of one element is therefore a relevant limiting factor. One of the deadliest disturbances of water ecosystems is the accelerated production of biomass what leads to significant changes in natural balance and relations. These changes eventually lead to accelerat- ed eutrophication which significantly shortens the life span of that particular water ecosystem. If there are no contra measures, or remediation measures, the consequences of increased saprobity get apparent and unpredictable. Due to constant increase of the total capacity via the increased saprobity, one of the most extreme consequences – the algal bloom is most probable, when the rapid multiplication of algae results in their visible apperance on the water surface (Bellinger and Sigee 2010). Blooming cyanobacteria might be very hazardous for whole ecosystem, but specially endangered are humans supplied with drinking water produced from blooming reservoirs and lakes (Svir~ev et al. 2009; Svir~ev et al. 2010; Dolinaj et al. 2011). There are numerous missinterepretations of the stated definitions in the literature, what has lead to erroneous applications of the saprobic system in detection of the water quality (review on the matter can be found in Krsti} et al. 2007). In order to establish the link between ecoremediation, total capacity, sapro- bity and eutrophication of the water ecosystems, we present the following comments. In a case that the water ecosystem has such a primary organic production that corresponds in the inten- sity to the decomposition of the total biomass, the trophy (white circle T, Fig. 3) is about the same as saprobity (black circle S, Fig. 3 – the white and the black circle are same in size). The quantity of mineral matter in this system, which is utilized in the process of photosynthesis, is nearly equal to the quantity of mineral salts produced after the degradation of organic matter of the dead primary producers and food chain mem- bers. In those systems, there is no additional organic load and the aging process corresponds to the natural eutrophication. 183 Zorica Svir~ev, Svetislav Krsti}, Tamara Vaì}, The phylosophy and applicability of ecoremediations for the protection of water ecosystems T Fo F o o d c o h d c a h ian TOTAL i CAPACITY BIOMASS CONSUMERS Natural eutrophication S Figure 3: The elements and procceses of natural eutrophication (T – trophy; S – saprobity). By entering of organic matter and mineral elements of whatever origin into the water ecosystem (human input or natural process), a certain amount of organic matter is decomposed, or the mineral salts are direct- ly incorporated into the total capacity (Fig. 4 – the black circle is larger than the white circle). In both cases, there is an increase of the total capacity what results in increasing of the total organic production. The quan- tity of the newly generated biomass in the water ecosystem can no longer be attributed to the trophy, but more to the overall photosynthesis in the system, what increases the biomass of both primary producers and the food chain members (Fig. 4). Due to total biomass increase in the water body, similar amount of organic matter or equivalent amount of mineral matter enters the decomposition processes as in the case of immediate input of external matters into the system (Fig. 4). In fact, the self-purification process actu- ally means that the water ecosystem successfully decomposes the organic matter. Nevertheless, a self-purification which will reverse the organic input on the quality and especially quantity level prior to organic load is impos- sible process. It is therefore recommendable to replace the term self-purification with more adequate expression, OP Fo F o o d c o h d c a h ian TOTAL i CAPACITY BIOMASS CONSUMERS Natural eutrophication >S Figure 4: The elements and procceses of accelerated eutrophication (OP – organic production; S – saprobity) 184 Acta geographica Slovenica, 54-1, 2014 OP ERM ERM III sanation ERM IV sanation Food chain TOTAL CAPACITY BIOMASS CONSUMERS Control ed eutrophication DECOMPOSERS 45°. Among the relative relief class- es, the highest W were obtained for the classes 50–100 and 100–150 m. Significantly lower total weights ij were obtained for certain classes of other influence factors as a result of the small number of occurrences 195 Radislav To{i}, Slavoljub Dragi}evi}, Matija Zorn, Novica Lovri}, Landslide susceptibility zonation: A case study of the Municipality … Table 2: Influence factors and their total weights for methods used. Factor Class Method IBM (weight) SIM (weight) LSA (weight) Lithology Fluvial sediments 8 –2.0931 –45.8778 Torrential sediments 16 –2.9685 –49.6415 Slope material 48 0.8982 76.1437 Flysch 32 0.1634 9.2904 Neogene sediments (sands, clays and marl) 48 1.0309 94.3779 Mesozoic rocks (limestone, dolomite 8 0.0180 0.9520 and diabase-hornstone rock) Land cover / Built-up area 18 –2.2699 –46.9237 land use Degraded surface 18 –0.5753 –22.8933 Green urban surface 18 0.0000 –52.3303 Arable surface 18 0.2961 18.0339 Orchard and vineyards 54 1.4348 167.3904 Deciduous-coniferous, mixed forest 9 0.3088 18.9361 Meadows and pastures 27 1.4394 168.3982 Water areas 0 0.0000 –52.3303 Slope (°) 0–5 10 –2.5878 –48.3959 5–15 40 0.6827 51.2448 15–45 30 0.7990 64.0188 > 45 20 –0.7458 –27.5076 Aspect Flat 3 0.0000 –52.1821 N 3 –0.2967 –13.4332 NE 6 –0.3552 –15.6449 E 3 –0.4195 –17.9294 SE 9 0.0916 5.0174 S 9 0.6529 48.2031 SW 9 0.5071 34.5626 W 9 0.2545 15.1636 NW 3 –0.0034 –0.1750 Relative relief (m) 0–50 16 –0.6465 –24.9169 50–100 20 0.8462 69.6348 100–150 12 0.8647 71.9157 150–200 8 0.0000 –36.5691 200–250 4 0.0000 –52.3303 Distance 0–50 3 0.1014 5.5834 from faults (m) > 50 6 –0.0122 –0.6341 Distance from 0–50 3 0.1116 6.1782 streams (m) > 50 6 –0.0333 –1.7136 Curvature Convex 8 0.4078 26.3475 (profile curvature) Concave 12 0.4725 31.6107 Flat 4 –0.0931 –4.6532 Elevation: 100–150 2 0.0000 –52.3303 meters (m) 150–200 2 –0.8977 –31.0047 200–250 6 1.1264 109.0864 250–300 4 1.0017 90.1619 300–350 4 0.3205 19.7734 350–400 2 0.0000 –29.4239 400–450 2 0.0000 –52.3303 Seismic zone 7.5 6 0.6989 52.9379 (MCS–64) 8 9 0.1199 6.6685 8.5 3 –0.9694 –32.4804 Figure 3: Thematic maps of influence factors used for creating landslide susceptibility maps. p 196 Acta geographica Slovenica, 54-1, 2014 ) S-64)C 0–50 50–100 100–150 150–200 200–250 elative relief (m ic zone (M R 7.5 8 8.5 Seism 2 2 1 km 1 km 0 0 E W 2 E SE S SW W N 1 spect Flat N N km A 0 eters above see levelm 2 – 1 100–150 150–200 200–250 250–300 300–350 350–400 400–450 km ltitude 0 A 2 1 km 0 Slope (degrees) 0–5 5–15 15–45 > 45 2 1 km oncave onvex 0 C Flat urvature (Profile curvature) C C ) s (m ixed forestm body stream up area ods– s and pastures eadow ater areas– 0–50 egraded surface reen urban surface rable surface rchard and vineyards reenw D G A O G M W istance fromD Land cover/land use Built– 2 2 1 km 1 km 0 0 ) ents ents faults (m ents aterial 0–50 > 50 eogene sedim esozoic rocks istance from Torrential sedim Slope m Flysch N M D Lithology Fluvial sedim 2 2 1 km 1 km 0 0 197 Radislav To{i}, Slavoljub Dragi}evi}, Matija Zorn, Novica Lovri}, Landslide susceptibility zonation: A case study of the Municipality … Landslide susceptibility Landslide susceptibility Landslide susceptibility index (IBM) index (SIM) index (LSA) High: 210 High: 7.15 High: 631.80 0 1 2 km 0 1 2 km 0 1 2 km Low: 47 Low: –10.90 Low: –315.52 Figure 4: Landslide susceptibility index maps of the study area obtained with Index-Based Method (IBM), Statistical Index Method (SIM), and Landslide Susceptibility Analysis (LSA). 100 90 ) 80 70 Very high 60 landslide susceptibility 50 40 30 High landslide ulative percentage of observed landslide occurrence (% 20 Moderate landslide susceptibility susceptibility Cum Low landslide susceptibility 10 0 –200 –100 0 100 200 300 400 500 600 LSI value (LSA) Figure 5: Cumulative percentage of observed landslides versus ranked LSI values resulting from the Index-Based Method (IBM), the Statistical Index Method (SIM), and Landslide Susceptibility Analysis (LSA). 198 Acta geographica Slovenica, 54-1, 2014 Landslide susceptibility (IBM) Landslide susceptibility (SIM) Landslide susceptibility (LSA) Low Low Low Moderate Moderate Moderate High High High 0 1 2 km Very high 0 1 2 km Very high 0 1 2 km Very high Landslide Landslide Landslide Figure 6: Landslide susceptibility zonation maps based on the Index-Based Method (IBM), Statistical Index Method (SIM), and Landslide Susceptibility Analysis (LSA). of landslides in these classes. According to the relative importance (expressed in total weight), the main instability factors are lithology, land cover / land use, slope, and relative relief. After calculating the weights for all influence factors, the weights were applied to create the landslide susceptibility index maps (LSI) for every method used (Figure 4). The integration of various influence fac- tors and classes in a single LSI is accomplished using a procedure based on the weighted linear sum, Equation 3. The LSI maps were compared to the landslide inventory map and the cumulative percentage of observed landslide values versus ranked LSI values were calculated (Figure 5). Three cut-off (»threshold«) percentages of observed landslides in the cumulative curve were used to identify the LSI scale value and four land- slide susceptibility classes: low, moderate, high, and very high (Figure 6). The final 1 : 10,000 susceptibility map is a raster grid with 5 × 5 meter cells. According to the meth- ods used, the high and very high susceptibility classes range (together) from 25.06 to 48.07% of the study area. Areas with these classes are distributed in the peripheral part of the study area. Low and moderate susceptibility classes range from 51.93 to 74.94% (Table 3). Table 3: Comparison of different landslide susceptibility zonation methods. INDEX-BASED METHOD (IBM) LSI-classes LSI scale value Area (km2) Area (%) Low susceptibility 47 to 101 28.08 50.37 Moderate susceptibility 101 to 135 13.69 24.57 High susceptibility 135 to 165 12.27 22.01 Very high susceptibility 165 to 210 1.70 3.05 STATISTICAL INDEX METHOD (SIM) LSI-classes LSI scale value Area (km2) Area (%) Low susceptibility –10.90 to –7.78 15.32 27.48 Moderate susceptibility –7.78 to –3.96 13.63 24.45 High susceptibility –3.96 to 0.71 9.81 17.61 Very high susceptibility 0.71 to 7.15 16.98 30.46 LANDSLIDE SUSCEPTIBILITY ANALYSIS (LSA) LSI-classes LSI scale value Area (km2) Area (%) Low susceptibility –315.52 to –114.91 24.92 44.71 Moderate susceptibility –114.91 to 81.98 9.75 17.50 High susceptibility 81.98 to 264.02 11.96 21.46 Very high susceptibility 264.02 to 631.80 9.10 16.33 199 Radislav To{i}, Slavoljub Dragi}evi}, Matija Zorn, Novica Lovri}, Landslide susceptibility zonation: A case study of the Municipality … Table 4: Summary of the prediction accuracy of the final landslide susceptibility zonation maps. Method Number of landslides observed Area of landslides observed Good Bad Good Bad Number % Number % km2 % km2 % IBM 173 80.09 43 19.91 2.1785 74.67 0.7392 25.33 SIM 216 100.00 0 0.00 2.9041 99.53 0.0136 0.47 LSA 207 95.83 9 4.17 2.7893 95.60 0.1284 4.40 Susceptibility maps can be validated through comparison with the data obtained from a terrain sur- vey. The quality of the landslide susceptibility method can be ascertained using the same landslide data used for the estimate, or by using independent landslide information that was not used for the assess- ment (e.g., Irigaray 1999; Remondo et al. 2003; Guzzeti et al. 2006; Zorn and Komac 2007). In order to select the final map of landslide susceptibility zonation, a cross validation technique was used to com- pare known landslide location data with the landslide susceptibility zonation map. In the study, we considered landslide prediction to be »good« if at least part of the landslide is in a »high« or »very high« suscepti- bility zone, and landslide prediction to be »bad« if at least part of the landslide is in a »low« or »moderate« susceptibility zone. Using SIM, all of the 216 landslides observed had good prediction, whereas using LSA 2 09 of the 216 landslides observed had good prediction, and only nine had bad prediction (Table 4). Furthermore, using the IBM method 74.67% area of the landslides observed belong to the »high« and »very high« susceptibility class, whereas using the SIM and LSA methods 99.53% and 95.60% area of the land- slides observed belong to the »high« and »very high« susceptibility class (Table 4). The validation of our susceptibility assessment suggests that the application of a relatively simple method- ology like IBM yields results that are quite different from those based on statistical methods. Although the input data were the same, it was shown that the use of IBM yields less reliable results, which is basically relat- ed to the subjectivity of the analysis, especially in defining weight coefficients for individual influence factors (e.g., van Westen et al. 1999; Fernández et al. 1999; Remondo et al. 2003; Guzzetti et al. 2006; Zorn and Komac 2008). The validation of the two statistical methods showed that they provide more accurate results. However, it should not be forgotten that the validation was carried out with the same set of landslide data that were used for the calculation and that the best way to check the accuracy of our final landslide sus- ceptibility zonation maps would be using independent landslide data. 5 Conclusion In the Municipality of Banja Luka, instable areas have significantly increased due to urbanization in land- slide-prone areas. The study identified 216 landslides with a total area of 2.92 km2 (5.2% of the municipality). In the study, three methods for landslide susceptibility zonation (IBM, SIM, and LSA) were applied to study the interrelations among the landslides observed and landslide influence factors. Crucial factors for landslide susceptibility in the study area are lithology, land cover / land use, slope, and relative relief. According to lithology, two units are the most important: slope and Neogene sediments. The most important topographic factor is slope angle, especially from 5 to 15°. Land use has a significant impact on instability, especially in orchards, vineyards, meadows, and pastures, as a result of direct or indi- rect human activity. Other factors are of less importance, as indicated by the value of the total weight of these factors, or the weight of individual classes within the influence factors. The results obtained show that statistical methods are important for creating landslide susceptibili- ty maps and that an empirical method (IBM) can provide less accurate results, but can be useful when available data are limited (as in Bosnia and Herzegovina). These study results can be used for better urban planning and landslide assessment purposes in Bosnia and Herzegovina, although they can be less useful at the site-specific scale (or microscale), where a geo-tech- nical approach has some preference. 200 Acta geographica Slovenica, 54-1, 2014 6 Acknowledgments The authors would like to acknowledge the support of Ministry of Science and Technology of Republika Srpska for funding the project »Landslide susceptibility zoning: Urban area of the Municipality of Banja Luka.« 7 References Aleotti, P., Chowdhury, R. 1999: Landslide hazard assessment: summary review and new perspectives. Bulletin of engineering geology and the environment 58-1. DOI: http://dx.doi.org/10.1007/s100640050066 Anbalagan, R. 1992: Landslide hazard evaluation and zonation mapping in mountainous terrain. Engineering geology 32-4. DOI: http://dx.doi.org/10.1016/0013-7952(92)90053-2 Barredo, J. I., Benavides, A., Hervas, J., van Westen, C. J. 2000: Comparing heuristic landslide hazard assess- ment techniques using GIS in the Tirajana basin, Gran Canaria Island, Spain. International journal of applied earth observation and geoinformation 2-1. DOI: http:/ dx.doi.org/10.1016/S0303-2434(00)85022-9 Burlica, C., Vukorep, I. 1980: Soil map of Bosnia and Herzegovina in scale 1 : 500,000. Sarajevo. Carrara, A., Cardinali, M., Detti, R., Guzzetti, F., Pasqui, V., Reichenbach, P. 1991: GIS techniques and statistical models in evaluating landslide hazard. Earth surface processes and landforms 16-5. DOI: http://dx.doi.org/0.1002/esp.3290160505 Carrara, A., Cardinali, M., Guzzetti, F., Reichenbach, P. 1995: GIS technology in mapping landslide haz- ard. Geographical information systems in assessing natural hazards. Dordrecht. Cevik, E., Topal, T. 2003: GIS-based landslide susceptibility mapping for a problematic segment of the nat- ural gas pipeline, Hendek (Turkey). Environmental geology 44-8. DOI: http://dx.doi.org/10.1007/ s00254-003-0838-6. Clerici, A., Perego, S., Tellini, C., Vescovi, P. 2002: A procedure for landslide susceptibility zonation by the con- ditional analysis method. Geomorphology 48-4. DOI: http:/ dx.doi.org/10.1016/S0169-555X(02)00079-X CORINE Land cover 1: Methodology. European environment agency, 1994. Internet: http:/ www.eea.europa.eu/ publications/COR0-part1 (4. 11. 2012). Crozier, M. J., Glade, T. 2005: Landslide hazard and risk: Issues, concepts, and approach. Landslide hazard and risk. DOI: http://dx.doi.org/10.1002/9780470012659.ch1 Dragi}evi}, S., Carevi}, I., Kostadinov, S., Novkovi}, I., Abolmasov, B., Milojkovi}, B., Simi}, D. 2012: Landslide susceptibility zonation in the Kolubara river basin (western Serbia) – Analysis of input data. Carpathian journal of earth and environmental sciences 7-2. Fernández, C. I., Del Castillo, T. F., Hamdouni, R. E., Montero, J. C. 1999: Verification of landslide susceptibility mapping. A case study. Earth surface processes and landforms 24-6. DOI: http://dx.doi.org/10.1002/ (SICI)1096-9837(199906)24:6<537::AID-ESP965>3.0.CO;2-6 Foumelis, M., Lekkas, E., Parcharidis, I. 2004: Landslide susceptibility mapping by GIS-based qualitative weight- ing procedure in Corinth area. Bulletin of 10th International congress of the Geological society 36-2. Guzzetti, F., Carrara, A., Cardinali, M., Reichenbach, P. 1999: Landslide hazard evaluation: a review of curent techniques and their application in a multi-scale study, Central Italy. Geomorphology 31, 1-4. DOI: http://dx.doi.org/10.1016/S0169-555X(99)00078-1 Guzzetti, F., Reichenbach, P., Ardizzone, F., Cardinali, M., Galli, M. 2006: Estimating the quality of land- slide susceptibility models. Geomorphology 81, 1-2. DOI: http:/ dx.doi.org/10.1016/j.geomorph.2006.04.007 Komac, B., Zorn, M., Gavrilov, M. B., Markovi}, S. B. 2013: Natural hazards – some introductory thoughts. Acta geographica Slovenica 53-1. DOI: http://dx.doi.org/10.3986/AGS53300 Luzi, L., Pergalani, F. 1999: Slope instability in static and dynamic conditions for urban planning: the šOltre Po Pavese’ case history (Regione Lombardia – Italy). Natural hazards 20-1. DOI: http://dx.doi.org/ 10.1023/A:1008162814578 Magliulo, P., Di Lisio, A., Russo, F., Zelano, A. 2008: Geomorphology and landslide susceptibility assess- ment using GIS and bivariate statistics: a case study in southern Italy. Natural hazards 47-3. DOI: http://dx.doi.org/10.1007/s11069-008-9230-x Moji}evi}, M., Vilovski, S., Tomi}, B., Pami}, J. 1976: Geological map of Banja Luka in scale 1 : 100,000. Belgrade. 201 Radislav To{i}, Slavoljub Dragi}evi}, Matija Zorn, Novica Lovri}, Landslide susceptibility zonation: A case study of the Municipality … Nagarajan, R., Mukherjee, A., Roy, A., Khire, M. V. 1998: Temporal remote sensing data and GIS applica- tion in landslide hazard zonation of part of Western Ghat, India. International journal of remote sensing 19-4. DOI: http://dx.doi.org/10.1080/014311698215865 Oztekin, B., Topal, T. 2005: GIS-based detachment susceptibility analyses of a cut slope in limestone, Ankara–Turkey. Environmental geology 49-1. DOI: http://dx.doi.org/10.1007/s00254-005-0071-6 Peri}, J., Arsovski, M., ]iri}, D., Vilovski, S., Siko{ek, B. 1971: Detaljna inènjersko-geolo{ka i geomehani~ka istraìvanja urbanog podru~ja Banje Luke. Sarajevo. Remondo, J., González, A., Díaz De Terán, J. R., Cendrero, A., Fabbri, A., Cheng, C. F. 2003: Validation of landslide susceptibility maps: examples and applications from a case study in Northern Spain. Natural Hazards 30-3. DOI: http://dx.doi.org/10.1023/B:NHAZ.0000007201.80743.fc Saha, A. K., Gupta, R. P., Arora, M. K. 2002: GIS-based landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas. International journal of remote sensing 23-2. DOI: http://dx.doi.org/10.1080/ 01431160010014260 Santacana, N., Baeza, B., Corominas, J., De Paz, A., Marturiá, J. 2003: A GIS-Based multivariate statisti- cal analysis for shallow landslide susceptibility mapping in La Pobla de Lillet area (Eastern Pyrenees, Spain). Natural hazards 30-3. DOI: http://dx.doi.org/10.1023/B:NHAZ.0000007169.28860.80 Süzen, M. L., Doyuran, V. 2004: A comparison of the GIS based landslide susceptibility assessment methods: multivariate versus bivariate. Environmental geology 45-5. DOI: http:/ dx.doi.org/10.1007/s00254-003-0917-8 To{i}, R., Dragi}evi}, S., Lovri}, N. 2012: Assessment of soil erosion and sediment yield changes using erosion potential method – Case study: Republic of Srpska-BiH. Carpathian journal of earth and envi- ronmental sciences 7-4. To{i}, R., Kapovi}, M., Lovri}, N., Dragi}evi}, S. 2013: Assessment of soil erosion potential using RUSLE and GIS: A case study of Bosnia and Herzegovina. Fresenius environmental bulletin 22-11a. Trkulja, D. 1998: Erathquakes of Banja Luka Region. Banja Luka. Turrini, M. C., Visintainer, P. 1998: Proposal of a method to define areas of landslide hazard and appli- cation to an area of the Dolomites, Italy. Engineering geology 50, 3-4. DOI: http://dx.doi.org/10.1016/ S0013-7952(98)00022-2 van Westen, C. J. 1994: GIS in landslide hazard zonation: A review, with examples from the Andes of Colombia. Mountain environments and geographic information systems. London. van Westen, C. J. 1997: Statistical landslide hazard analysis. Application Guide, ILWIS 2.1 for Windows. Enschede. van Westen, C. J., Lulie Getahun, F. 2003: Analyzing the evolution of the Tessina landslide using aerial photographs and digital elevation models. Geomorphology 54, 1-2. DOI: http://dx.doi.org/10.1016/ S0169-555X(03)00057-6 van Westen, C. J., Rengers, N., Terlien, M. T. J., Soeters, R. 1997: Prediction of the occurrence of slope insta- bility phenomena through GIS-based hazard zonation. Geologische Rundschau 86-2. DOI: http:/ dx.doi.org/ 10.1007/s005310050149 van Westen, C. J., Seijmonsbergen, A. C., Mantovani, F. 1999: Comparing landslide hazard maps. Natural hazards 20, 2-3. Amsterdam. DOI: http://dx.doi.org/10.1023/A:1008036810401 Vilovski, S. 1970: Osnovna geolo{ka karta, list Banja Luka 1 : 25,000. Sarajevo. Voogd, H. 1983: Multi-criteria evaluation for urban and regional planning. London. Wati, S. E., Hastuti T., Widjojo, S., Pinem, F. 2010: Landslide susceptibility mapping with heuristic approach in mountainous area: A case study in Tawangmangu sub district Central Java, Indonesia. International archives of the photogrammetry, remote sensing and spatial information science 38-8. Zorn, M., Komac, B. 2004: Deterministic modeling of landslide and rockfall risk. Acta geographica Slovenica 44-2. DOI: http://dx.doi.org/10.3986/AGS44203 Zorn, M., Komac, B. 2007: Probability modelling of landslide hazard. Acta geographica Slovenica 47-2. DOI: http://dx.doi.org/10.3986/AGS47201 Zorn, M., Komac, B. 2008: Zemeljski plazovi v Sloveniji. Georitem 8. Ljubljana. Zorn, M., Komac, B. 2009: The importance of landsliding in a flysch geomorphic system: The example of the Gori{ka brda hills (W Slovenia). Zeitschrift für Geomorphologie, Suppl. 53-2. DOI: http:/ dx.doi.org/ 10.1127/0372-8854/2009/0053S3-0057 Zorn, M., Komac, B. 2011: Damage caused by natural disasters in Slovenia and globally between 1995 and 2010. Acta geographica Slovenica 51-1. DOI: http://dx.doi.org/10.3986/AGS51101 202 Acta geographica Slovenica, 54-1, 2014 Guidelines for Contributing Authors in Acta Geographica Slovenica – Geografski Zbornik 1 Aims and scopes Acta geographica Slovenica – Geografski zbornik is the main Slovenian geographical scientific journal pub- lished by the Anton Melik Geographical Institute of the Scientific Research Centre of the Slovenian Academy of Sciences and Arts. The journal is aimed at presentation of scientific articles from the fields of physical, human and region- al geography. Review scientific articles are published, e.g. review and synthesis of already published articles on specific topic, and original research articles, e.g. first publication of original scientific results that allows repetition of the study and examination of results. The journal was first published in 1952, and fourteen issues appeared periodically until 1976. Granted more permanent government funding, it has been published annually since 1976. From 2003, it is pub- lished twice a year. The journal is subsequently published in print and on the Internet in both Slovenian and English since 1994 (http://ags.zrc-sazu.si/). Each year, it is distributed in exchange for 200 scientific journals from around the world. The articles on the internet are read in more than 100 countries. Acta geographica Slovenica – Geografski zbornik welcomes articles from all geographers in Slovenia, South-Eastern and Central Europe, as well as articles from those in related fields whose scientific and research work can enrich the overall view of the geographical environment. Acta geographica Slovenica publishes articles in Slovenian and English. If one of the authors is from Slovenia the article has to be in English and Slovenian. The articles of the authors from abroad and the arti- cles of special issues are only published in English. The articles in Slovenian have to be translated to English after a positive peer-review. If the article is translated by the editorial board the cost for authors is 500 . If the authors provide a professional translation of the article it has to be lectored; the cost of lectoring for authors is 200 . Slovenian articles are lectored by the editorial board. The articles that are submitted for publication in English need to be lectored after a positive peer-review. Lectoring is organized by the edi- torial board; the cost for authors is 200 . 2 Article components The articles published in the scientific journal Acta geographica Slovenica – Geografski zbornik should be arranged according to the IMRAD scheme: Introduction, Method, Results And Discussion or by the Guidelines for scientific journals and scientific articles published by the Slovenian research agency which financial- ly supports the Acta geographica Slovenica journal. The articles must contain the following elements: • article's main title in both English and Slovenian; • abstract (up to 800 characters including spaces); • up to eight key words; • article in English (up to 20,000 characters including spaces) and identical article in Slovenian; • reference list. Text of the article should be equal in Slovenian and English. The titles of chapters and subchapters in the article should be marked with ordinal numbers (for exam- ple, 1 Introduction, 1.1 Methodology, 1.2 Terminology). The division of an article into chapters is obligatory, but authors should use subchapters sparingly. It is recommended that the article include Introduction, Conclusion and References chapters. The titles should be short and comprehensible. Authors should avoid using footnotes and endnotes. 3 Quoting When quoting from source material, authors should state the author's last name and the year, separate indi- vidual sources with semicolons, order the quotes according to year, and separate the page information from 203 Acta geographica Slovenica, 54-1, 2014 the author's name and year information with a comma, for example »(Melik 1955, 11)« or »(Melik, Ile{i~ and Vri{er 1963; Kokole 1974, 7 and 8)«.If the source material has more than three authors only the first one should be listed (Melik et al. 1956). The References' units should be listed according to the alphabetical order of the authors' second names. If there are more units from the same author in the same year, letters should be added to the citation (for example 1999a in 1999b). Every unit consists of three sentences. In the first Author's name, publishing year and article's title are listed in front of the colon while the title is listed after it. The surnames of the authors and the initials of their names are separated by commas. The subtitle is separated from the title by a comma. If the unit is an article, the name and number of the journal is indicated in the second sentence. If the unit is a monograph, there is no second sentence. The name of the publisher and number of pages are not listed. If the unit is not printed the type (e.g. diploma thesis) should be listed in the second sen- tence, separated from information of the institution by a comma. Laws should be qouted by a title, publication name and its number (e.g. Official gazette 56-2), separated from the publication year in the last part of the quotation. In the third sentence the place of publishing or the place where the publication is kept are stated. The Digital object identifier (DOI) has to be included to the quotes if available. For more details please visit webpage of the Crossref company (www.crossref.org; http:/ www.crossref.org/guestquery; http:/ dx.doi.org/). Few examples: 1) for articles in journals: • Melik, A. 1955a: Kra{ka polja Slovenije v pleistocenu. Dela In{tituta za geografijo 3. • Melik, A. 1955b: Nekaj glaciolo{kih opaànj iz Zgornje Doline. Geografski zbornik 5. • Perko, D. 2002: Dolo~anje vodoravne in navpi~ne razgibanosti povr{ja z digitalnim modelom vi{in. Geografski vestnik 74-2. • Fridl, J., Urbanc, M., Pipan, P. 2009: The importance of teachers' perception of space in education. Acta geographica Slovenica 49-2. DOI: http://dx.doi.org/10.3986/AGS49205 2) for chapters in monographs or articles in proceedings: • Lovren~ak, F. 1996: Pedogeografska regionalizacija Spodnjega Podravja s Prlekijo. Spodnje Podravje s Prlekijo, 17. zborovanje slovenskih geografov. Ljubljana. • Mihevc, B. 1998: Slovenija na starej{ih zemljevidih. Geografski atlas Slovenije. Ljubljana. • Komac, B., Zorn, M. 2010: Statisti~no modeliranje plazovitosti v dràvnem merilu. Od razumevanja do upravljanja, Naravne nesre~e 1. Ljubljana. 3) for monographs: • Natek, K., Natek, M. 1998: Slovenija, Geografska, zgodovinska, pravna, politi~na, ekonomska in kul- turna podoba Slovenije. Ljubljana. • Fridl, J., Kladnik, D., Perko, D., Oroèn Adami~, M. 1998: Geografski atlas Slovenije. Ljubljana. • Perko, D., Oroèn Adami~, M. 1998: Slovenija – pokrajine in ljudje. Ljubljana. • O{tir, K. 2006: Daljinsko zaznavanje. Ljubljana. 4) for expert's reports, diploma, master and doctoral thesis: • Richter, D. 1998: Metamorfne kamnine v okolici Velikega Tinja. Diplomsko delo, Pedago{ka fakulteta Univerze v Mariboru. Maribor. • [ifrer, M. 1997: Povr{je v Sloveniji. Elaborat, Geografski in{titut Antona Melika ZRC SAZU. Ljubljana. 5) for sources with unkwnown authors and cartographic sources: • Popis prebivalstva, gospodinjstev, stanovanj in kme~kih gospodarstev v Republiki Sloveniji, 1991 – kon~ni podatki. Zavod Republike Slovenije za statistiko. Ljubljana, 1993. • Digitalni model vi{in 12,5. Geodetska uprava Republike Slovenije. Ljubljana, 2005. • Dràvna topografska karta Republike Slovenije 1 : 25.000, list Breìce. Geodetska uprava Republike Slovenije. Ljubljana, 1998. • Franciscejski kataster za Kranjsko, k.o. Sv. Agata, list A02. 1823–1869. Arhiv Republike Slovenije. Ljubljana. • Buser, S. 1986a: Osnovna geolo{ka karta SFRJ 1 : 100.000, list Tolmin in Videm (Udine). Zvezni geolo{ki zavod. Beograd. • Buser, S. 1986b: Osnovna geolo{ka karta SFRJ 1 : 100.000, tolma~ lista Tolmin in Videm (Udine). Zvezni geolo{ki zavod. Beograd. 204 Acta geographica Slovenica, 54-1, 2014 6) for internet sources with known authors and/or titles: • Vilhar, U. 2010: Fenolo{ka opazovanja v okviru Intenzivnega spremljanja stanja gozdnih ekosistemov. Internet: http://www.gozdis.si/impsi/delavnice/Fenoloska%20opazovanja_Vilhar.pdf (19. 2. 2012). • eGradiva, 2010. Internet: http://www.egradiva.si/ (11. 2. 2012). 7) for internet sources with unknown authors: • Internet: http://giam.zrc-sazu.si/ (22. 7. 2012). 8) for more internet sources with unknown authors • Internet 1: http://giam.zrc-sazu.si/ (22. 7. 2012). • Internet 2: http://ags.zrc-sazu.si/ (22. 7. 2012). In case 7) the author is quoted in the text, for example (Vilhar 2010), while in case 8) only internet is quoted, for example (Internet 2). The laws are cited as follows (name of the law, number of the official gazzette, place of publishing), for example: • Zakon o kmetijskih zemlji{~ih. Uradni list Republike Slovenije 59/1996. Ljubljana. • Zakon o varstvu pred naravnimi in drugimi nesre~ami. Uradni list Republike Slovenije 64/1994, 33/2000, 87/2001, 41/2004, 28/2006 in 51/2006. Ljubljana. If amemdments were proposed to the law they have to be quoted. In the text whole title of the law has to be quoted or its first few words if the title is a long one, for example (Zakon o kmetijskih zemlji{~ih 1996) ali (Zakon o varstvu … 1994). All the quoted contributions have to be listed in the chapter References. The authors should consider copyright rules of data owners, for example: the rules of the Geodetic survey of the Republic of Slovenia are available at http://e-prostor.gov.si/fileadmin/narocanje/pogoji_ uporabe_podpisani.pdf. 4 Tables and figures Authors should submit photographs and other graphic materials in a form suitable for scanning or in digital raster form with a resolution of 300 dpi, preferably in TIFF or JPG format formats in the printing size. If authors cannot deliver articles or graphic supplements prepared using the specified programs, they should consult the editorial board in advance: rok.ciglicazrc-sazu.si. All tables in the article should be numbered uniformly and have their own titles. The number and the text are separated by a colon, the caption is ended by a full stop. Example: Table 1: Number of inhabitants of Ljubljana. Table 2: Spreminjanje povpre~ne temperature zraka v Ljubljani (Velkavrh 2009). The tables should contain no formatting and should not be too large – one-page tables are appreciated. All illustrative material – Figures (photographs, maps, graphs, etc.) in the article should also be num- bered uniformly and have their own titles. Example: Figure 1: Location of measurement points along the glacier. The journal has an established 16.5 cm × 23.5 cm format to which all graphic materials must be adapt- ed. In the case of graphic illustrations for which the authors do not have the copyright, the authors must acquire permission to publish from the copyright owner. Authors must include the author's name with the title of the illustration. Illustrative material should be precisely 134mm wide (one page) or 64mm wide (half page, one coloumn), height should not exceed 200 mm. If the figure is to be the size of the page, its size should be 134 × 192,3 mm (the subtitle is written in one line) or 134 × 200 mm (the subtitle is on the facing page). Maps should be done in digital vector form using the Corel Draw program, and charts done using Corel Draw or Adobe Illustrator programs, especially if they contain text. They can also be done in digi- tal raster form with resolution at least 300 dpi, preferably in TIFF or JPG formats in the printing size. For maps made using CorelDraw or Adobe Illustrator programs,two separate files should be prepared; the original file (format .cdr or .ai) and the file with representation of the image (format .jpg). For maps made using ArcGIS where raster layers were used next to vector layers (for example .tif of relief, airborne or satellite image), three files should be submitted: a file with vector image with not transparency used together with a legend and colophone (export in format.ai), the second file with raster image (export 205 Acta geographica Slovenica, 54-1, 2014 in .tif format), and the third one with vector and raster image together showing the final version of the map (export in format .jpg). No title should be printed on maps as they are written below them. The colors should be saved in CMYK and not in RGB or other formats. The Times new roman font, size 8, should be used to write the legend, as well as for colophon (size 6). In the colophon author, scale, source and copyright should be listed. The colophone should be written in both, English and Slovenian, if space is available on the map. Example: Scale/merilo: (grafi~no, tekstovno) Author of contents/avtor vsebine: Drago Perko Author of map/avtorica zemljevida: Jerneja Fridl Source/vir: Statistical office of the Republic of Slovenia, 2002 © Anton Melik geographical institute ZRC SAZU, 2005 Graphs should be done in digital form using Excel program. Graphs should be done on separated sheets and accompanied by data. Photographs have to be in raster format and in resolution 240 dots per cm or 600 dots per inch, prefer- ably in.tif or .jpg formats, that is about 3200 dots per page width of the journal. Figures showing computer screen should be prepared at the highest possible screen resolution (Nadzorna plo{~a Vsi elementi nadzorne plo{~e Zaslon Lo~ljivost zaslona oziroma Control Panel All Control Panel Items Display Screen Resolution). The figure is done by print screen, the data are pasted prilepi to the select- ed graphic programme (e.g. Paint) and saved as .tif. The size of the image or its resolution should not be changed.You can find templates of maps in cdr and mxd files for a whole page map in landscape view and an example of correct structure of files for a submission of a map made with ESRI ArcGIS on the journal webpage. 5 Article admission Only original and new articles will be accepted for publication. Upon acceptance of your chapter, you will be required to sign a warranty that your article is original (contents–wording and formatting) and has not been submitted for publication or published elsewhere. Authors must submit their contributions in digital form written in Word format. The Word file name should contain author’s second name (for example: novak.doc), while the figures should be named with a number following the order of figures in the article (for example: figure01.tif, figure02.cdr, figure12.ai, figure17.xls). Supplementary files (figures) can be submitted packed in one zip file. The digital file should be unformatted, except for text written in bold and italic form. As the article is subject to changes during the review process it should first be submitted in either English or Slovenian language, and translated to the other language only after the acceptance for publication. The translation is an expense of the author. The entire text should be written in lowercase (except for uppercase initial letters, of course) with- out unnecessary abbreviations and contractions. The text should be plain and only bold and italic formatting is allowed. Please use no other formatting, such as chapter or page numbering. Authors of articles must enclose a scanned (or rewritten), completed, and signed Registration Form containing the author's agreement to abide by the rules for publication in Acta geographica Slovenica – Geografski zbornik. The Registration Form shall serve as acceptance letter and author's contract. The reg- istration form is available on-line: ags.zrc-sazu.si. If a text is unsatisfactorily written, the editorial board can return it to the author to arrange to have the text proofread professionally or reject the publication of the article. Date of acceptance of the article for publication is published after the abstract and key words. Authors should send articles to the editor-in-chief: Blà Komac Anton Melik Geographical Institute ZRC SAZU Gosposka ulica 13, SI – 1000 Ljubljana, Slovenia E-mail: blaz.komacazrc-sazu.si 206 Acta geographica Slovenica, 54-1, 2014 6 Review process All articles are examinated by one of the editors upon receipt. Afterwards the authors are usually asked to correct or change the article. After the articles have been corrected they are sent to two anonymous reviewers. The reviewers receive an article without the author's name, and the author receives the review(s) without the reviewer's names. If the reviews do not require the article to be corrected or augmented, the review will not be sent to the author. If the size of the text fails to comply with the provisions for publication, the author shall allow the text to be appropriately modified according to the judgment of the publisher. The article may be rejected for publication by the reviewers or by the editors. 7 Copyright For articles sent for publication to Acta geographica Slovenica – Geografski zbornik, all the author's moral rights remain with the author, while the author's material rights to reproduction and distribution in the Republic of Slovenia and other states, are for no fee, for all time, for all cases, for unlimited editions, and for all media shall be unexclusively ceded to the publisher. The authors allow publication of the arti- cle or its components on the internet. Author has to provide a professional translation. The name of the translator should be quoted. Authors should cooperate in the reviewing and editorial process. Author gives permission to the publisher to change the article in order to be in accordance with the Guidelines, including the length of the article. The publisher shall see to it that all accepted articles are published in Acta geographica Slovenica – Geografski zbornik and on the internet in accordance with the submission time and with the arrangement according to the themes discussed. Ordered contributions can be published regardless of the submission time. No honoraria are paid for articles appearing in Acta geographica Slovenica – Geografski zbornik nor for the reviews. The author shall receive one (1) free copy of the publication. 8 Submission preparation checklist As part of the submission process, authors are required to check off their submission's compliance with all of the following items, and submissions may be returned to authors that do not adhere to these guidelines. 1. The submission has not been previously published, nor is it before another journal for consideration (or an explanation has been provided in Comments to the Editor). 2. The submission file is in Microsoft Word document file format. 3. Where available, URLs for the references have been provided. 4. The text is single-spaced; uses a 12-point font; employs italics, rather than underlining (except with URL addresses). All illustrations' and figures' locations within text are marked (illustrations and fig- ures are not inside text!). Illustrations and figures are provided as supplementary files (cdr, ai for maps and illustrations; tif for photographs). Tables are placed within the text at the appropriate points. Supplementary files must not excess 50 MB. 5. The text adheres to the stylistic and bibliographic requirements outlined in the Author Guidelines, which is found in About the Journal. 6. !! If submitting to a peer-reviewed section of the journal, the instructions in Ensuring a Blind Review have been followed. !! 7. Supplementary files do not exceed 50 MB. 9 Privacy statement The names and email addresses entered in this journal site will be used exclusively for the stated purposes of this journal and will not be made available for any other purpose or to any other party. 207 Acta geographica Slovenica, 54-1, 2014 10 Ordering Acta geographica Slovenica can be ordered at the publisher: Zalòba ZRC Novi trg 2, p. p. 306 SI – 1001 Ljubljana, Slovenija Phone: +386 (0)1 470 64 64 Fax: +386 (0)1 425 77 94 E-mail: zalozbaazrc-sazu.si The journal can be bought in the Azil bookshop, Novi trg 2, SI – 1000 Ljubljana, Slovenia or borrowed in the libraries (www.cobiss.si). 11 Acta geographica Slovenica Editorial review form Acta geographica Slovenica editorial review form 1 The paper is an original scientific one – the paper follows the standard IMRAD scheme and is original and the first presentation of research results with the focus on methods, theoretical aspects or case study.) Yes No 2 The paper's content is suitable for publishing in the AGS journal – the paper is from the field of geog- raphy or related fields of interest, the presented topic is interesting and well presented. In case of negative answer add comments below.) Yes No 3 Editorial notes regarding the paper's content. 4 Length of the paper is acceptable for further processing (20.000 characters including space). If longer, the paper has to be shortened by the author and resubmitted. • The paper has less than 20.000 characters. • The paper has more than 20.000 characters, but less than 25.000. • The paper has more than 25.000 characters. 5 The style and formatting of the paper is according to the AGS guidelines – the paper is prepared in plain text, no other text formatting is used than bold and italic. See the Guidelines of AGS journal for details.) Yes No 6 Notes regarding style and formatting. 7 Citing in the paper is according to the AGS guidelines and style, including DOI identificators. Yes No 8 The reference list is suitable (the author cites previously published papers with similar topic from other relevant scientific journal). Yes, the author cited previously published papers on similar topic. No, the author did not cite previously published papers on similar topic. 9 Scientific language of the paper is appropriate and understandable. Yes No 208 Acta geographica Slovenica, 54-1, 2014 10 Supplementary files (ai, cdr, pdf, tif, jpg, xlsx etc.) that were added to the paper are in proper format and resolution (including the introductory photo), maps are prepared according to the AGS Guidelines. (In this step contact the technical editor rok.ciglicazrc-sazu.si for assistance if needed).* • Supplementary files are correct. • Supplementary files are not appropriate and need a major correction. • Some supplementary files need corrections. 11 Describe the possible deficiencies of the supplementary files: 12 DECISION OF THE RESPONSIBLE EDITOR* The paper is accepted for further processing and may be sent to the reviewer. The paper is accepted for further processing but needs technical improvements (see notes). The paper is accepted for further processing but its content needs additional improvements (see notes). The paper is not accepted for publication because: • It is more suitable for a specialized journal. • Does not fit the aims and scopes of the AGS journal. • Is not an original scientific paper. • The presentation of the results is poor. • The paper is of very low quality. • The paper has already been published elsewhere. • Other (see comments below). • Other reasons for rejection of the paper. 12 Acta geographica Slovenica review form 1 RELEVANCE 1a) Are the findings original and the paper is therefore a significant one?* yes no partly 1b) Is the paper suitable for the subject focus of the AGS journal?* yes no 2 SIGNIFICANCE 2a Does the paper discuss an important problem in geography or related fields?* yes no partly 2b Does it bring relevant results for contemporary geography?* yes no partly 2c What is the level of the novelty of research presented in the paper?* high middle low 209 Acta geographica Slovenica, 54-1, 2014 3 ORIGINALITY 3a Has the paper been already published or is too similar to work already published?* yes no 3b Does the paper discuss a new issue?* yes no 3c Are the methods presented sound and adequate?* yes no partly 3d Do the presented data support the conclusions?* yes no partly 4 CLARITY 4a Is the paper clear, logical and understandable?* yes no 4b If necessary, add comments and recommendations to improve the clarity of the title, abstract, keywords, introduction, methods or conclusion:* 5 QUALITY 5a Is the paper technically sound? (If no, the author should discuss technical editor rok.ciglicazrc-sazu.si for assistance.)* yes no 5b Does the paper take into account relevant current and past research on the topic?* yes no Propose amendments, if no is selected: 5d Is the references list the end of the paper adequate?* yes no Propose amendments, if no is selected: 5e Is the quoting in the text appropriate?* yes no partly Propose amendments, if no is selected: 5f Which tables are not necessary? 5g Which figures are not necessary? 210 Acta geographica Slovenica, 54-1, 2014 6 COMMENTS OF THE REVIEWER Comments of the reviewer on the contents of the paper: Comments of the reviewer on the methods used in the paper: 7 RECOMMENDATION OF THE REVIEWER TO THE EDITOR-IN-CHIEF My recommendation is: Please rate the paper from 1 low to 100 high : Personal notes of the reviewer to editor-in-chief. 211 Acta geographica Slovenica, 54-1, 2014 Na vo di la avtor jem za pri pra vo ~lan kov v Acti geo grap hi ci Slo ve ni ci – Geo graf skem zbor ni ku 1 Uvod Acta geo grap hi ca Slo ve ni ca – Geo graf ski zbor nik je osred nja slo ven ska znans tve na revi ja za geo gra fi jo, ki jo izda ja Geo graf ski in{ti tut Anto na Meli ka Znans tve no ra zi sko val ne ga cen tra Slo ven ske aka de mi je zna - no sti in umet no sti. Re vi ja je name nje na pred sta vi tvi znans tve nih dosè kov s po dro~ ja fizi~ ne, drù be ne in regio nal ne geo - gra fi je ter sorod nih ved. Objav lja pre gled na znans tve na bese di la, to je pre gled in sin te zo è objav lje nih naj no vej {ih del o do lo ~e ni temi, ter izvir na znans tve na bese di la, to je prvo obja vo ori gi nal nih razi sko val - nih rezul ta tov v tak {ni obli ki, da se razi ska va lah ko pono vi, ugo to vi tve pa pre ve ri jo. Re vi ja je prvi~ iz{ la leta 1952 in je do leta 1976, ko je bila natis nje na {ti ri naj sta {te vil ka, izha ja la ob~a - sno. Leta 1976 je zara di traj nej {e finan~ ne pomo ~i drà ve za~e la izha ja ti red no, od leta 2003 pa izha ja dva krat let no v ti ska ni in elek tron ski obli ki na med mrè ju. Od leta 1994 izha ja ena ko vred no v slo ven skem in angle{ - kem jezi ku (http://ags.zrc-sazu.si). Vsa ko leto jo raz po{ lje mo v iz me nja vo na ve~ kot 200 na slo vov po celem sve tu. ^lan ke na med mrè ju bere jo v ve~ kot 100 dr à vah sve ta. Acta geo grap hi ca Slo ve ni ca – Geo graf ski zbor nik v ob ja vo spre je ma geo graf ske ~lan ke iz Slo ve ni je ter Jugovz hod ne in Sred nje Evro pe. Objav lja mo tudi ~lan ke geo gra fi ji sorod nih ved, kate rih znans tve no in razi sko val no delo lah ko obo ga ti geo graf ske pogle de na pokra ji no. Acta geo grap hi ca Slo ve ni ca objav lja ~lan ke v slo ven skem in angle{ kem jezi ku. ^lan ki, pri kate rih je vsaj eden od avtor jev iz Slo ve ni je, mora jo ime ti tudi slo ven ski pre vod. ^lan ki avtor jev iz tuji ne in ~lan ki poseb nih izdaj so objav lje ni samo v an gle{ kem jezi ku. ^lan ke, ki pris pe jo v slo ven skem jezi ku, je po pozi - tiv ni recen zi ji tre ba pre ve sti v an gle{ ~i no. ^e za pre vod poskr bi ured ni{ tvo, je stro {ek pre vo da za avtor je 500 . ^e avtor ji sami poskr bi jo za pro fe sio nal ni pre vod ~lan ka, je tre ba ~la nek lek to ri ra ti, stro {ek lek ture v vi {i ni 200  pa nosi jo avtor ji. Za lek tu ro slo ven ske ga dela ~lan ka poskr bi ured ni{ tvo. ^lan ke, ki pris pe - jo v an gle{ kem jezi ku, je po pozi tiv ni recen zi ji tre ba nuj no lek to ri ra ti. Za lek tu ro poskr bi ured ni{ tvo, stro {ek v vi {i ni 200  pa nosi jo avtor ji. 2 Sesta vi ne ~lan ka ^lan ki, objav lje ni v znans tve ni revi ji Acta geo grap hi ca Slo ve ni ca – Geo graf ski zbor nik so ure je ni po she - mi IMRAD (uvod, meto da, rezul ta ti in raz pra va; angl.: Intro duc tion, Met hod, Results And Dis cus sion) ozi ro ma v skla du z na vo di li o ob li ko va nju perio di~ ne pub li ka ci je kot celo te in ~lan ka kot nje ne ga sestav ne ga dela, ki jih je izda la Agen ci ja za razi sko val no dejav nost Repub li ke Slo ve ni je, ki denar no pod pi ra izha ja nje. ^lan ki, posla ni v ob ja vo, mora jo ime ti nasled nje sesta vi ne: • glav ni naslov v slo ven skem in angle{ kem jezi ku; • izvle ~ek dol ì ne do 800 zna kov sku paj s pre sled ki; • do osem klju~ nih besed; • ~la nek v an gle{ kem ali slo ven skem jezi ku, ki naj sku paj s pre sled ki obse ga do 20.000 zna kov. • sez nam upo rab lje nih virov in lite ra tu re, ure jen v skla du z na vo di li. Be se di lo ~lan kov mora biti ena ko vred no v an gle{ kem in slo ven skem jezi ku. ^la nek naj ima naslo ve pogla vij in naslo ve pod po gla vij ozna ~e ne z vr stil ni mi {tev ni ki (na pri mer: 1 Uvod, 1.1 Me to do lo gi ja, 1.2 Ter mi no lo gi ja). Raz de li tev ~lan ka na poglav ja je obvez na, pod po glav ja pa naj avtor upo ra bi le izje mo ma. Zaè le no je, da ima ~la nek poglav ja Uvod, Sklep in Lite ra tu ra. Naslo vi ~lan kov naj bodo jasni in ~im kraj {i. Avtor ji naj se izog ne jo pisa nju opomb pod ~rto na kon cu stra ni in naj bodo zmer - ni pri upo ra bi tujk. 3 Citi ra nje v ~lan ku Av tor naj pri citi ra nju med bese di lom nave de prii mek avtor ja, let ni co ter po potre bi {te vil ko stra ni. Ve~ cita tov se lo~i s pod pi~ jem in raz vr sti po let ni cah, naved bo stra ni pa se od priim ka avtor ja in let ni ce lo~i 212 Acta geographica Slovenica, 54-1, 2014 z ve ji co, na pri mer: (Me lik 1955, 11) ali (Me lik, Ile {i~ in Vri {er 1963, 12; Koko le 1974, 7 in 8). ^e ima citi - ra no delo ve~ kot tri avtor je, se citi ra le prve ga avtor ja, na pri mer (Me lik s sod. 1956, 217). Eno te v po glav ju Viri in lite ra tu ra naj bodo nave de ne po abe ced nem redu priim kov avtor jev, eno te iste - ga avtor ja pa raz vr{ ~e ne po let ni cah. ^e je v sez na mu ve~ enot iste ga avtor ja iz iste ga leta, se let ni cam doda jo ~rke (na pri mer 1999a in 1999b). Zapis vsa ke citi ra ne eno te sklad no s slo ven skim pra vo pi som sestav lja jo tri - je stav ki. V pr vem stav ku sta nave de na avtor in let ni ca izi da (~e je avtor jev ve~, so lo~e ni z ve ji co, z ve ji co sta lo~e na tudi prii mek avtor ja in za~et ni ca nje go ve ga ime na, med za~et ni co avtor ja in let ni co ni veji ce), sle di dvo - pi~ je, za njim pa naslov in more bit ni pod na slov, ki sta lo~e na z ve ji co. ^e je citi ra na eno ta ~lanek, se v dru gem stav ku nave de pub li ka ci ja, v ka te ri je ~la nek natis njen, ~e pa je eno ta samo stoj na knji ga, drugega stav ka ni. Izda ja te lja, zalò ni ka in stra ni se ne nava ja. ^e eno ta ni tiska na, se v dru gem stav ku nave de vrsta eno te (na pri mer ela bo rat, diplom sko, magi str sko ali dok tor sko delo), za veji co pa {e usta no va, ki hra ni to eno to. V tret - jem stav ku se za tiska ne eno te nave de kraj izda je, za neti ska ne pa kraj hra nje nja. Pri nava ja nju lite ra tu re, ki je vklju ~e na v si stem DOI (Di gi tal Object Iden ti fier), je tre ba na kon cu navedbe doda ti tudi {te vil ko DOI. [te vil ke DOI so dode lje ne posa mez nim ~lan kom serij skih pub li ka cij, pris pev kom v mono gra fi jah in knji gam. [te vil ko DOI naj de te v sa mih ~lan kih in knji gah, ozi ro ma na splet ni stra ni http:/ www.cros sref.org/guest query. Ne kaj pri me rov (lo ~i la so upo rab lje na sklad no s slo ven skim pra vo pi som): 1) za ~lan ke v re vi jah: • Melik, A. 1955a: Kra{ ka polja Slo ve ni je v plei sto ce nu. Dela In{ti tu ta za geo gra fi jo 3. Ljub lja na. • Melik, A. 1955b: Nekaj gla cio lo{ kih opa ànj iz Zgor nje Doli ne. Geo graf ski zbor nik 5. Ljub lja na. • Per ko, D. 2002: Dolo ~a nje vodo rav ne in nav pi~ ne raz gi ba no sti povr{ ja z di gi tal nim mode lom vi{in. Geo graf ski vest nik 74-2. Ljub lja na. • Fridl, J., Urbanc, M., Pipan, P. 2009: The im por tan ce of teac hers' per cep tion of spa ce in edu ca tion. Acta geo grap hi ca Slo ve ni ca 49-2. Ljub lja na. DOI: 10.3986/AGS49205 2) za poglav ja v mo no gra fi jah ali ~lan ke v zbor ni kih: • Lovren ~ak, F. 1996: Pedo geo graf ska regio na li za ci ja Spod nje ga Podrav ja s Pr le ki jo. Spod nje Podravje s Pr le ki jo, 17. zbo ro va nje slo ven skih geo gra fov. Ljub lja na. • Mihevc, B. 1998: Slo ve ni ja na sta rej {ih zem lje vi dih. Geo graf ski atlas Slo ve ni je. Ljub lja na. • Komac, B., Zorn, M. 2010: Sta ti sti~ no mode li ra nje pla zo vi to sti v dr àv nem meri lu. Od razu me vanja do uprav lja nja, Narav ne nesre ~e 1. Ljub lja na. 3) za mono gra fi je: • Natek, K., Natek, M. 1998: Slo ve ni ja, Geo graf ska, zgo do vin ska, prav na, poli ti~ na, eko nom ska in kulturna podo ba Slo ve ni je. Ljub lja na. • Fridl, J., Klad nik, D., Per ko, D., Oro èn Ada mi~, M. (ur.) 1998: Geo graf ski atlas Slo ve ni je. Ljub lja na. • Per ko, D., Oro èn Ada mi~, M. (ur.) 1998: Slo ve ni ja – pokra ji ne in ljud je. Ljub lja na. • O{tir, K. 2006: Daljin sko zaz na va nje. Ljub lja na. 4) za ela bo ra te, diplom ska, magi str ska, dok tor ska dela ipd.: • Rich ter, D. 1998: Meta morf ne kam ni ne v oko li ci Veli ke ga Tinja. Diplom sko delo, Peda go{ ka fakulteta Uni ver ze v Ma ri bo ru. Mari bor. • [ifrer, M. 1997: Povr{ je v Slo ve ni ji. Ela bo rat, Geo graf ski in{ti tut Anto na Meli ka ZRC SAZU. Ljubljana. 5) za vire brez avtor jev in kar to graf ske vire: • Popis pre bi vals tva, gos po dinj stev, sta no vanj in kme~ kih gos po dar stev v Re pub li ki Slo ve ni ji, 1991 – kon~ ni podat ki. Zavod Repub li ke Slo ve ni je za sta ti sti ko. Ljub lja na, 1993. • Digi tal ni model vi{in 12,5. Geo det ska upra va Repub li ke Slo ve ni je. Ljub lja na, 2005. • Dràv na topo graf ska kar ta Repub li ke Slo ve ni je 1 : 25.000, list Bre ì ce. Geo det ska upra va Repub li ke Slo ve ni je. Ljub lja na, 1998. • Fran cis cej ski kata ster za Kranj sko, k.o. Sv. Aga ta, list A02. 1823–1869. Arhiv Repub li ke Slo ve ni je. Ljubljana. • Buser, S. 1986a: Osnov na geo lo{ ka kar ta SFRJ 1 : 100.000, list Tol min in Videm (Udi ne). Zvez ni geo - lo{ ki zavod. Beo grad. • Buser, S. 1986b: Osnov na geo lo{ ka kar ta SFRJ 1 : 100.000, tol ma~ lista Tol min in Videm (Udi ne). Zvezni geo lo{ ki zavod. Beo grad. Av tor ji vse pogo ste je citi ra jo vire z med mrè ja. ^e sta zna na avtor in/ali naslov citi ra ne eno te, potem se jo nave de tako le (da tum v ok le pa ju pome ni ~as ogle da med mrè ne stra ni): • Vil har, U. 2010: Feno lo{ ka opa zo va nja v ok vi ru Inten ziv ne ga sprem lja nja sta nja gozd nih eko si ste mov. Med mrè je: http://www.goz dis.si/imp si/de lav ni ce/Fe no lo ska%20opa zo va nja_Vil har.pdf (19. 2. 2010). • e Gra di va, 2010. Med mrè je: http://www.egra di va.si/ (11. 2. 2010). 213 Acta geographica Slovenica, 54-1, 2014 ^e avtor ni poz nan, se nave de le: • Med mrè je: http://giam.zrc-sazu.si/ (22. 7. 2011). ^e se nava ja ve~ enot z med mrè ja, se doda {e {te vil ko: • Med mrè je 1: http://giam.zrc-sazu.si/ (22. 7. 2011). • Med mrè je 2: http://zgs.zrc-sazu.si/ (22. 7. 2011). Med bese di lom se v pr vem pri me ru nave de avtor ja, na pri mer (Vil har 2010), v dru gem pri me ru pa le med mrè je, na pri mer (med mrè je 2). Za ko ne se citi ra v na sled nji obli ki (ime zako na, {te vil ka urad ne ga lista, kraj izi da), na pri mer: • Zakon o kme tij skih zem lji{ ~ih. Urad ni list Repub li ke Slo ve ni je 59/1996. Ljub lja na. • Zakon o vars tvu pred narav ni mi in dru gi mi nesre ~a mi. Urad ni list Repub li ke Slo ve ni je 64/1994, 33/2000, 87/2001, 41/2004, 28/2006 in 51/2006. Ljub lja na. ^e ima zakon dopol ni tve, je tre ba nave sti tudi te. Med bese di lom se zakon nava ja s ce lim ime nom, ~e gre za kraj {e ime, ali pa z ne kaj prvi mi bese da mi in tre mi pika mi, ~e gre za dalj {e ime. Na pri mer (Za kon o kme tij skih zem lji{ ~ih 1996) ali (Za kon o vars tvu … 1994). V po glav ju Viri in lite ra tu ra mora jo biti nave de na vsa dela, citi ra na v pris pev ku, osta lih, neci ti ra nih del pa naj avtor ne nava ja. Av tor ji naj upo {te va jo tudi navo di la za nava ja nje virov last ni ka podat kov ali posred ni ka, ~e jih le-ta dolo ~a. Pri mer: Geo det ska upra va Repub li ke Slo ve ni je ima navo di la za nava ja nje virov dolo ~e na v do ku - men tu »Po go ji upo ra be geo det skih podat kov« (http://e-pro stor.gov.si/fi lead min/na ro ca nje/po go ji_upo ra be_ pod pi sa ni.pdf). 4 Pre gled ni ce in gra fi~ ne pri lo ge v ~lan ku Pri lo ge mora jo prav tako odda ti natis nje ne v di gi tal ni obli ki v us trez nem for ma tu. Foto gra fi je in dru ge gra fi~ ne pri lo ge mora jo avtor ji, ~e je le mogo ~e, odda ti v ob li ki, pri mer ni za ske ni ra nje, sicer pa v di gital - ni rastr ski obli ki z lo~ lji vost jo vsaj 300 pik na palec ali 120 pik na cm, naj bo lje v for ma tu TIFF ali JPG in kon~ ni veli ko sti sli ke. ^e avtor ji ne more jo odda ti pris pev kov in gra fi~ nih pri log, pri prav lje nih v omenjenih pro gra mih, naj se pred hod no pos ve tu je jo z ured ni{ tvom (rok.ci glicazrc~-sazu.si). Vse pre gled ni ce v ~lan ku so o{te vil ~e ne in ima jo svo je naslo ve. Med {te vil ko in naslo vom je dvo pi~je. Naslov kon ~a pika. Pri mer: Pre gled ni ca 1: [te vi lo pre bi val cev Ljub lja ne po posa mez nih popi sih. Pre gled ni ca 2: Spre mi nja nje pov pre~ ne tem pe ra tu re zra ka v Ljub lja ni (Vel ka vrh 2009). Vse gra fi~ ne pri lo ge – Sli ke (fo to gra fi je, zem lje vi di, gra fi in podob no) v ~lan ku so o{te vil ~e ne enotno in ima jo svo je naslo ve. Med {te vil ko in naslo vom je dvo pi~ je. Naslov kon ~a pika. Pri me ra: Sli ka 1: Rast {te vi la pre bi val cev Ljub lja ne po posa mez nih popi sih. Sli ka 2: Izsek topo graf ske kar te v me ri lu 1 : 25.000, list Kranj. Av tor ji mora jo za gra fi~ ne pri lo ge, za kate re nima jo avtor skih pra vic, pri lo ì ti foto ko pi jo dovo lje nja za obja vo, ki so ga pri do bi li od last ni ka avtor skih pra vic. Gra fi~ ne pri lo ge naj bodo {iro ke to~ no 134 mm (cela {iri na stra ni) ali 64 mm (pol {iri ne, 1 stol pec), viso ke pa naj ve~ 200 mm. V pri me ru, da èli mo ime ti celo stran sko sli ko ali zem lje vid, mora biti nju na veli - kost 134 × 192,3 mm (pod na pis h gra fi~ ni pri lo gi je eno vr sti ~en) ali 134 × 200 mm (pod na pis h gra fi~ ni pri lo gi je nave den na sosed nji stra ni). Sli kov no gra di vo (zem lje vi di, she me in podob no) naj bo v for ma tih .ai ali .cdr, foto gra fi je pa v for - ma tih .tif ali .jpg. Zem lje vi di naj bodo izde la ni v di gi tal ni obli ki. Zaè le no je, da so odda ni v vek tor ski obli ki, pri prav - lje ni s pro gra mom Corel Draw ali Ado be Illu stra tor, zla sti ~e vse bu je jo bese di lo. Mò no jih je odda ti tudi v ra str ski obli ki z lo~ lji vost jo vsaj 300 pik na palec ali 120 pik na cm, naj bo lje v for ma tu TIFF ali JPG in kon~ ni veli ko sti sli ke. Pri tistih zem lje vi dih in she mah, izde la nih s pro gra mom Arc GIS, kjer so poleg vek tor skih slo jev kot pod la ga upo rab lje ni tudi rastr ski slo ji (na pri mer .tif relie fa, letal ske ga ali sate lit ske ga posnet ka in podob - no), oddaj te tri lo~e ne dato te ke. V prvi naj bodo samo vek tor ski slo ji z iz klju ~e no more bit no pro soj nost jo poli go nov sku paj z le gen do in kolo fo nom (iz voz v for ma tu .ai), v dru gi samo rastr ska pod la ga (iz voz v for - ma tu .tif), v tret ji, kon trol ni dato te ki pa vek tor ski in rastr ski slo ji sku paj, tako kot naj bi bil vide ti kon~ ni zem lje vid v knji gi (iz voz v for ma tu .jpg). To je nuj no, da tudi natis nje ni zem lje vid ohra ni ustrez no kakovost. 214 Acta geographica Slovenica, 54-1, 2014 Zem lje vi di naj bodo brez naslo va, ker je nave den v pod na pi su. Pri izbi ri in dolo ~a nju barv za sli kov ne pri lo ge upo ra bi te zapis CMYK in ne RGB ozi ro ma dru gih. Za legen do zem lje vi da je potreb no upo ra bi ti tip pisa ve Times new roman veli ko sti 8 pik, za kolo fon pa isto vrsto pisa ve veli ko sti 6 pik. V ko lo fo nu naj so po vrsti od zgo raj navz dol v an gle{ kem in slo ven - skem jezi ku nave de ni: meri lo (gra fi~ no ali tek stov no), avtor vse bi ne, avtor zem lje vi da, vir in usta no va ozi ro ma nosi lec avtor skih pra vic. Kolo fon mora biti v an gle{ kem in slo ven skem jezi ku razen kjer to zara di prostor - skih ome ji tev ni mò no. Pri mer: Sca le/me ri lo: (gra fi~ no, tek stov no) Aut hor of con tents/av tor vse bi ne: Dra go Per ko Aut hor of map/av to ri ca zem lje vi da: Jer ne ja Fridl Sour ce/vir: Sta ti sti~ ni urad RS, 2002 © Geo graf ski in{ti tut Anto na Meli ka ZRC SAZU, 2005 Pri zem lje vi dih in she mah, izde la nih v pro gra mih Corel Draw ali Ado be Illu stra tor, oddaj te dve lo~eni dato te ki; poleg ori gi nal ne ga zapi sa (for mat .cdr ali .ai) dodaj te {e dato te ko, ki pri ka zu je, kako naj bo vide ti sli ka (for mat .jpg). Gra fi naj bodo izde la ni s pro gra mom Excel. Na posa mez nem listu naj bodo sku paj z gra fom tudi podat - ki, na pod la gi kate rih je bil izde lan. Fo to gra fi je mora avtor odda ti v di gi tal ni rastr ski obli ki z lo~ lji vost jo vsaj 240 pik na cm ozi ro ma 600 pik na palec, naj bo lje v for ma tu .tif ali .jpg, kar pome ni prib lì no 3200 pik na celo {iri no stra ni v re vi ji. Sli ke, ki pri ka zu je jo ra~u nal ni{ ki zaslon, mora jo biti nare je ne pri naj ve~ ji mò ni lo~ lji vo sti zaslo na (lo~ lji vost ure di mo v: Nad zor na plo{ ~a Vsi ele men ti nad zor ne plo{ ~e Za slon Lo~ lji vost zaslo na ozi ro ma Con trol Panel All Con trol Panel Items Dis play Screen Reso lu tion). Sli ko se nato pre pro sto nare di s pri - ti skom tip ke print screen, pri le pi v iz bran gra fi~ ni pro gram (na pri mer Sli kar, Paint) in shra ni kot .tif. Pri tem se sli ke ne sme pove ~a ti ali pomanj {a ti ozi ro ma ji spre me ni ti lo~ lji vost. Po èlji lah ko upo ra bi te tudi ustrez ne pro gra me za zajem zaslo na in shra ni te sli ko v za pi su .tif. 5 Spre je ma nje pris pev kov Za obja vo v Acti geo grap hi ci Slo ve ni ci spre je ma mo le izvir ne ozi ro ma nove znanstv ne ~lan ke. Avtor s pod pi som potr di izja vo o iz vir no sti vse bi ne in podo be ~lan ka ter dejs tvo, da ~la nek {e ni bil posre dovan v ob ja vo dru gam ozi ro ma drug je ni è bil objav ljen. Av tor ji mora jo bese di lo pris pev kov odda ti v di gi tal ni obli ki (na disku, zgo{ ~en ki ali po elek tron ski po{ti), zapi sa ne s pro gra mom Word. Wor dov doku ment naj avtor naslo vi s svo jim priim kom (na pri mer: novak.doc), sli kov ne pri lo ge pa z opisom priloge in {te vil ko pri lo ge, ki ustre za vrst ne mu redu pri log med bese di lom (na pri mer: slika01.tif, slika02.cdr, slika12.ai, preglednica17.xls). Za ra di more bit nih spre memb v po stop ku recen zi je in ure ja nja naj ~la nek naj prej odda jo v slo ven skem jezi ku, po spre je mu za obja vo pa {e v an gle{ kem. Pre vod je stro {ek avtor ja. Di gi tal ni zapis bese di la naj bo povsem eno sta ven, brez zaple te ne ga obli ko va nja, samo dej nih naslo - vov, porav na ve desne ga roba, delje nja besed, pod ~r ta va nja in podob ne ga. Avtor ji naj ozna ~i jo le mast ni (krep ki) in leè ~i tisk. Bese di lo naj bo v ce lo ti izpi sa no z ma li mi ~rka mi (ra zen veli kih za~et nic, seve da), brez nepo treb nih kraj {av, okraj {av in kra tic. Av tor ji ~lan kov mora jo pri lo ì ti pre sli ka no (pre pi sa no ali natis nje no), izpol nje no in pod pi sa no Pri - jav ni co, v ok vi ru kate re je tudi izja va, s ka te ro potr ju je jo, da se stri nja jo s pra vi li obja ve v Acti geo grap hi ci Slo ve ni ci – Geo graf skem zbor ni ku. Pri jav ni ca nado me{ ~a sprem ni dopis in avtor sko pogod bo. Pri jav ni - ca je na voljo tudi na med mrè ni stra ni Acte geo grap hi ce Slo ve ni ce – Geo graf ske ga zbor ni ka: ags.zrc-sazu.si. ^e bese di lo slov ni~ no ali vse bin sko ni ustrez no napi sa no, ga ured ni{ ki odbor avtor ju lah ko vrne v po - pra vek, zah te va lek to ri ra nje ali ~la nek zavr ne. Datum pre jet ja ~lan ka je objav ljen za angle{ kim pre vo dom izvle~ ka in klju~ nih besed. Av tor ji naj pris pev ke po{i lja jo na naslov glav ne ga ured ni ka: Blà Komac Geo graf ski in{ti tut Anto na Meli ka ZRC SAZU Gos po ska uli ca 13, SI – 1000 Ljub lja na, Slo ve ni ja E-po {ta: blaz.ko macazrc-sazu.si. 215 Acta geographica Slovenica, 54-1, 2014 6 Recen zi ra nje ~lan kov ^lan ke naj prej pre gle da eden od podro~ nih ured ni kov. Avtor ji ~lan kov so potem obi ~aj no pozva ni, da ~la nek ustrez no dopol ni jo ali popra vi jo. Sle di recen zent ski posto pek, ki je pra vi lo ma ano ni men. Recenzen - ta prej me ta ~la nek brez naved be avtor ja ~lan ka, avtor ~lan ka pa prej me recen zi jo brez naved be recen zen ta. ^e recen zi ja ne zah te va poprav ka ali dopol ni tve ~lan ka, se avtor ju ~lan ka recen zij ne po{ lje. Avtor dovolju - je, da ured ni{ tvo pris pe vek kraj {a ali dru ga ~e pri la go di, da bo pri me ren za obja vo. Na pred log ured ni{ tva ali recen zen ta se lah ko zavr ne obja vo pris pev ka. 7 Avtor ske pra vi ce Za avtor sko delo, posla no za obja vo v Acti geo grap hi ci Slo ve ni ci – Geo graf skem zbor ni ku, vse moral ne avtor - ske pra vi ce pri pa da jo avtor ju, mate rial ne avtor ske pra vi ce repro du ci ra nja in distri bui ra nja v Re pub li ki Slo ve ni ji in v dru gih drà vah pa avtor brez pla~ no, enkrat za vse lej, za vse pri me re, za neo me je ne nakla - de in za vse medi je neiz klju~ no pre ne se na izda ja te lji co. Avtor dovo lju je obja vo ~lan ka ali nje go vih delov na med mrè ju. Av tor sam poskr bi za pro fe sio nal ni pre vod ~lan ka ter obvez no nave de ime in prii mek pre va jal ca. Avtor ji so dol` ni sode lo va ti v pro ce su lek to ri ra nja bese di la in ure ja nja ~lan ka. ^e obseg avtor ske ga dela ni v skla du z na vo di li za obja vo, avtor dovo lju je izda ja te lju, da avtor sko delo po svo ji pre so ji ustrez no pri la go di. Iz da ja telj poskr bi, da se vsi pris pev ki s po zi tiv no recen zi jo, ~e so zago tov lje na sreds tva za tisk, obja - vi jo v Acti geo grap hi ci Slo ve ni ci – Geo graf skem zbor ni ku in na med mrè ju, pra vi lo ma v skla du z vrst nim redom pris pet ja pris pev kov in v skla du z ena ko mer no raz po re di tvi jo pris pev kov po temah. Naro ~e ni pris - pev ki se lah ko obja vi jo ne gle de na datum pris pet ja. Pris pev ki v re vi ji Acta geo grap hi ca Slo ve ni ca – Geo graf ski zbor nik niso hono ri ra ni niti niso hono ri - ra ni recen zen ti. Av tor ju pri pa da 1 brez pla ~en izvod pub li ka ci je. 8 Pri pra va kon trol ne ga sez na ma v si ste mu OJS Kot del postop ka odda je ~lan ka mora jo avtor ji pre ve ri ti sklad nost ~lan ka in navo dil. Ured ni{ tvo si pri dr - ù je pra vi co, da avtor jem vrne ~la nek v po pra vek, ~e ta ni pri prav ljen sklad no s temi navo di li. Avtor ji mora jo upo {te va ti nasled nja navo di la: 1. ^la nek ni bil pred hod no objav ljen niti ni v po stop ku obja ve v dru gi revi ji ozi ro ma je to raz lo è no v ko - men tar ju ured ni ku). 2. Dato te ka je shra nje na v for ma tu Micro soft Word. 3. ^e so na voljo, so pred lo è ni URL-ji in DOI refe renc. 4. Bese di lo ima enoj ne raz mi ke s pi sa vo veli ko sti 12 to~k; za pou dar ja nje vse bi ne upo rab lja leè~ ali krepki for mat brez pod ~r to va nja (ra zen URL naslo vov). V be se di lu je s pod na pi si ozna ~e na lega slik, ilu stracije in sli ke pa niso vne se ne v be se di lo, tem ve~ so odda ne v po seb nih dato te kah (cdr, ai za zem lje vi de in ilu stra ci je; tif za foto gra fi je). Pre gled ni ce so na ustrez nih mestih bese di lu. Veli kost posa mez ne dodatne dato te ke ne sme pre se ~i 50 MB. 5. Bese di lo je pri prav lje no sklad no z ob li kov ni mi in bib lio graf ski mi meri li za pri pra vo ~lan kov za objavo v re vi ji Acta geo grap hi ca Slo ve ni ca, ki so objav lje ne v po glav ju About na splet ni stra ni http:/ ojs.zrc-sazu.si/ags. 6. Pri odda ji ~lan ka so bila upo {te va na navo di la za zago tav lja nje ano nim ne recen zi je ~lan ka. 7. Veli kost dodat nih dato tek ne pre se ga 50 MB. 9 Izja va o za seb no sti Ime na in e-po{t ne naslo ve, vne se ni v tej revi ji mestu se bodo upo rab lja li izklju~ no za nave de ne name ne te revi je in ne bodo na voljo za kakr {ne koli dru ge name ne ali za kate ro koli dru go stran ko. 216 Acta geographica Slovenica, 54-1, 2014 10 Naro ~a nje Acto geo grap hi co Slo ve ni co – Geo graf ski zbor nik lah ko naro ~i te na naslo vu zalò ni ka: Za lò ba ZRC Novi trg 2, p. p. 306 SI – 1001 Ljub lja na, Slo ve ni ja te le fon: +386 (0)1 470 64 64 faks: +386 (0)1 425 77 94 e-po {ta: zaloz baazrc-sazu.si Re vi jo je mogo ~e tudi kupi ti v knji gar ni Azil na Novem trgu 2 v Ljub lja ni ali si jo spo so di ti v knjì ni cah (www.co biss.si). 11 Obra zec za ured ni{ ki pre gled ~lan kov Obra zec za ured ni{ ki pre gled ~lan kov v re vi ji Acta geo grap hi ca Slo ve ni ca – Geo graf skem zbor ni ku je zara - di upo ra be ured ni{ ke ga siste ma Open jour nal system (OJS) dosto pen samo v an gle{ kem jezi ku. Glej angle{ ki del navo dil. 12 Obra zec za recen zi jo ~lan kov Obra zec za recen zi jo ~lan kov v re vi ji Acta geo grap hi ca Slo ve ni ca – Geo graf skem zbor ni ku je zara di upo - ra be ured ni{ ke ga siste ma Open jour nal system (OJS) dosto pen samo v an gle{ kem jezi ku. Glej angle{ ki del navo dil. 217 ISSN: 1581-6613 UDC – UDK: 91 ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKI ZBORNIK 54-1 2014 © Geografski in{titut Antona Melika ZRC SAZU, 2014 Print/tisk: Collegium Graphicum d. o. o. Ljubljana 2014 naslovnica 54-1_naslovnica 49-1.qxd 17.2.2015 9:15 Page 1 4 ACTA GEOGRAPHICA SLOVENICA 10 GEOGRAFSKI ZBORNIK 2 • 54-1 • 2014 ACTA GEOGRAPHICA -145 Contents – Vsebina • Wolfgang TINTOR, Maja ANDRI^ IK Lateglacial studies in the western valleys of the Italian Julian Alps and in the Koritnica valley 7 NR SLOVENICA GEOGRAFSKI ZBORNIK Mateja BREG VALJAVEC O Detection of former landfills in gravel plain using geomorphometric analysis and High-Resolution LiDAR DTM 21 B Odkrivanje prikritih odlagali{~ odpadkov v prodni ravnini z geomorfometri~no analizo in LiDAR DMR 34 I Z Smiljana \UKI^IN, Jasmina \OR\EVI], Jelena MILANKOVI] K Spatial and social changes caused by the continuous exploitation of lignite in the Kolubara lignite basin, Serbia 41 SF Tamara LUKI], Milka BUBALO - @IVKOVI], Bojan \ER^AN, Gordana JOVANOVI] A Population Growth in the Border Villages of Srem, Serbia 51 R Lilijana [PRAH, Tatjana NOVAK, Jerneja FRIDL G The wellbeing of Slovenia's population by region: comparison of indicators with an emphasis on health 67 O Blaginja prebivalcev Slovenije po regijah: primerjava kazalnikov s poudarkom na zdravju 80 EG Ivana CRLJENKO • Some older sources for Croatian exonym analysis 89 A Daniel TUDORA, Mihail EVA IC A geographical methodology for assessing nodality of a road network. Case study on the western Moldavia 101 N Josef NAVRÁTIL, Miha LESJAK, Kamil PÍCHA, Stanislav MARTINÁT, Jana NAVRÁTILOVÁ, E Vivian L. WHITE BARAVALLE GILLIAM, Jaroslav KNOTEK, Tomá{ KU^ERA, Roman [VEC, V Zuzana BALOUNOVÁ, Josef RAJCHARD O The importance of vulnerable areas with potential tourism development: L a case study of the Bohemian forest and South Bohemia tourism regions 115 SA Vera GLIGORIJEVI], Mirjana DEVED@I], Ivan RATKAJ Localization factors and development strategies for producer services: a case study of Belgrade, Serbia 131 ICHP Spe cial issue – Natu ral hazards 2014 A Slobodan B. MARKOVI], Albert RUMAN, Milivoj B. GAVRILOV, R Thomas STEVENS, Matija ZORN, Blà KOMAC, Drago PERKO G Modelling of the Aral and Caspian seas drying out influence to climate and environmental changes 143 OE Jelena KOVA^EVI] - MAJKI], Marko V. MILO[EVI], Milena PANI], Dragana MILJANOVI], Jelena ]ALI] G Risk education in Serbia 163 AT Zorica SVIR^EV, Svetislav KRSTI], Tamara VA@I] C The phylosophy and applicability of ecoremediations for the protection of water ecosystems 179 A Radislav TO[I], Slavoljub DRAGI]EVI], Matija ZORN, Novica LOVRI] Landslide susceptibility zonation: A case study of the Municipality of Banja Luka (Bosnia and Herzegovina) 189 ISSN 1581-6613 9 1 8 5 1 7 7 0 1 0 1 6 6 2014 54 1