Journal of Mountain Science

, Volume 16, Issue 5, pp 1005–1022 | Cite as

Spatial modelling of deforestation in Romanian Carpathian Mountains using GIS and Logistic Regression

  • Gheorghe Kucsicsa
  • Cristina DumitricăEmail author


Deforestation process represents a wide concern mainly in the mountain environments due to its role in global warming, biodiversity loss, land degradation and natural hazards occurrence. Thus, the present study is focused on the largest afforested landform unit of Romania and, consequently, the most affected area by forest losses: Carpathian Mountains. The main goal of the paper is to examine and analyze the various explanatory variables associated with deforestation process and to model the probability of deforestation using GIS spatial analysis and logistic regression. The forest cover for 1990 and 2012, derived from CORINE Land Cover (CLC) database, were used to quantify historical forest cover change included in the modelling. To explain the biophysical and anthropogenic effects, this study considered several explanatory factors related to local topography, forest cover pattern, accessibility, urban growth and population density. Using ROC (Receiver Operating Characteristic) and 500 controlling sampling points, the statistical and spatial validations were assessed in order to evaluate the performance of the resulted data. The analysis showed that the area experienced a continuous forest cover change, leading to the loss of over 250,000 ha of forested area during the period 1990–2012. The most significant influence of the explanatory factors of deforestation were noticed in case of distance to forest edge (β=−4.215), forest fragmentation (β=2.231), slope declivity (β=−1.901), elevation (β=1.734) and distance to roads (β=−1.713). The statistical and spatial validation indicates a good accuracy of the model with reasonably AUC (0.736) and Kappa (0.739) values. The model’s results suggest an intensification of the deforestation process in the area, designing numerous new clusters with high probability in the Apuseni Mountains, northern and central part of the Eastern Carpathians, western part of the Southern Carpathians and northern part of the Banat Mountains. The study could represent a useful outcome to identify the forests more vulnerable to logging and to adopt appropriate policies and decisions in forest management and conservation. In addition, the resulted probability map could be used in other studies in order to investigate potential environmental implications (e.g. geomorphological hazards or impact on biodiversity and landscape diversity).


Deforestation probability Romanian Carpathians Logistic Regression 


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The current research was elaborated in the framework of the research project framed into the research plan of the Institute of Geography, Romanian Academy: “The National Geographic Atlas of Romania”.

The authors would like to thank the European Environment Agency (Copernicus Land Monitoring Service) for the provision of CLC database ( cover/view). Map data copyrighted OpenStreetMap contributors and available from


  1. Ahmed B, Ahmed R, Zhu X (2013) Evaluation of model validation techniques in land cover dynamics. ISPRS International Journal of Geo-Information 2(3): 577–597. CrossRefGoogle Scholar
  2. Angelsen A (2008) How do we set the reference levels for REDD payments? In: Angelsen A (ed.), Moving Ahead with REDD, Issues, Options and Implications. Center for International Forestry Research (CIFOR), Bogor, Indonesia. pp 53–64. Google Scholar
  3. Arekhi S (2011) Modeling spatial pattern of deforestation using GIS and logistic regression: a case study of northern Ilam forests, Ilam province, Iran. African Journal of Biotechnology 10(72).
  4. Pir Bavaghar M (2015) Deforestation modelling using logistic regression and GIS. Journal of Forest Science 61(5): 193–199. CrossRefGoogle Scholar
  5. Bax V, Francesconi W, Quintero M (2016) Spatial modeling of deforestation processes in the central Peruvian amazon. Journal for Nature Conservation 29: 79–88. CrossRefGoogle Scholar
  6. Bălteanu D, Dumitraşcu M, Ciupitu D, et al. (2006) Protected natural areas. In: Bălteanu D, et al. (eds.), Romania. Space, Society, Environment. The Publishing House of the Romanian Academy. pp 328–339.Google Scholar
  7. Bălteanu D, Chendeş V, Sima M, et al. (2010) A country-wide spatial assessment of landslide susceptibility in Romania. Geomorphology 124(3–4): 102–112. CrossRefGoogle Scholar
  8. Bālteanu D, Sima M, Jurchescu M, et al. (2016a) Natural and technological hazards. In: Bălteanu D, et al. (eds.), Romania. Nature and Society. The Publishing House of the Romanian Academy. pp 563–592. (In Romanian)Google Scholar
  9. Bălteanu D, Năstase M, Dumitraşcu M, Grigorescu I (2016b) Environmental changes in the Maramureş Mountains Natural Park. In: Zhelezov G (ed.), Sustainable Development in Mountain Regions. Springer International Publishing Switzerland. pp 335–348. CrossRefGoogle Scholar
  10. Gurung AB, Bokwa A, Chełmicki W, et al. (2009) Global change research in the Carpathian Mountain region. Mountain Research and Development 29: 282–288. CrossRefGoogle Scholar
  11. Bogdan O, Dragotă C, Micu D (2016) Climatic potential. In: Bălteanu D, et al. (eds.), Romania. Nature and Society. The Publishing House of the Romanian Academy. pp 102–130. (In Romanian)Google Scholar
  12. Büttner G, Feranec J, Jaffrain G, et al. (2004) The CORINE land cover 2000 project. EARSeL eProceedings 3(3): 331–346.Google Scholar
  13. Clark WAV, Hosking PL (1986) Statistical Methods for Geographers. Wiley, New York.Google Scholar
  14. Cohen J (1960) A coefficient of agreement for nominal scales. Educational and Psychological Measurement 20(1): 37–46. CrossRefGoogle Scholar
  15. Drăghici CC, Andronache I, Ahammer H, et al. (2017) Spatial evolution of forest areas in the northern Carpathian Mountains of Romania. Acta Montanistica Slovaca 22(2): 95–106.Google Scholar
  16. Feranec J, Šúri M, Ot’Ahel’ J, et al. (2000) Inventory of major landscape changes in the Czech Republic, Hungary, Romania and Slovak Republic 1970s–1990s. International Journal of Applied Earth Observation and Geoinformation 2(2): 129–139. CrossRefGoogle Scholar
  17. Feranec J, Jaffrain G, Soukup T, et al. (2010) Determining changes and flows in European landscapes 1990–2000 using CORINE land cover data. Applied Geography 30(1): 19–35. CrossRefGoogle Scholar
  18. De Barros Ferraz SF, Capão LMSAC, Vettorazzi CA (2006) Temporal scale and spatial resolution effects on Amazon forest fragmentation assessment in Rondônia. International Journal of Remote Sensing 27(3): 459–472. CrossRefGoogle Scholar
  19. Freitas SR, Hawbaker TJ, Metzger JP (2010) Effects of roads, topography, and land use on forest cover dynamics in the Brazilian Atlantic Forest. Forest Ecology and Management 259(3): 410–417. CrossRefGoogle Scholar
  20. Fuller DO, Meijaard EM, Christy L, et al. (2010) Spatial assessment of threats to biodiversity within East Kalimantan, Indonesia. Applied Geography 30(3): 416–425. CrossRefGoogle Scholar
  21. Gaston G, Brown SA, Lorenzini M, et al. (1998) State and change in carbon pools in the forests of tropical Africa. Global Change Biology 4(1): 97–114. CrossRefGoogle Scholar
  22. Geist H, Lambin E (2001) What drives tropical deforestation? A meta-analysis of proximate and underlying causes of deforestation based on subnational case study evidence Land-Use and Land-Cover Change (LUCC) Project, International Geosphere-Biosphere Programme (IGBP). LUCC Report Series 4. p 116.Google Scholar
  23. Glade T (2003) Landslide occurrence as a response to land use change: a review of evidence from New Zealand. Catena 51(3–4): 297–314. CrossRefGoogle Scholar
  24. Gheţău V, Damian N, Simion M (2016) Population - demographic dynamics and structures. In: Bălteanu D, et al. (eds.), Romania. Nature and Society. The Publishing House of the Romanian Academy. pp 221–249. (In Romanian)Google Scholar
  25. Griffiths P, Kuemmerle T, Kennedy RE, et al. (2012) Using annual time-series of Landsat images to assess the effects of forest restitution in post-socialist Romania. Remote Sensing of Environment 118: 199–214. CrossRefGoogle Scholar
  26. Griffiths P, Kuemmerle T, Baumann M, et al. (2013a) Forest disturbances, forest recovery, and changes in forest types across the Carpathian ecoregion from 1985 to 2010 based on Landsat image composites. Remote Sensing of Environment 151: 72–88. CrossRefGoogle Scholar
  27. Griffiths P, Müller D, Kuemmerle T, et al. (2013b) Agricultural land change in the Carpathian ecoregion after the breakdown of socialism and expansion of the European Union. Environmental Research Letters 8. Google Scholar
  28. Grigorescu I, Geacu S (2017) The dynamics and conservation of forest ecosystems in Bucharest Metropolitan Area. Urban Forestry & Urban Greening 27: 90–99. CrossRefGoogle Scholar
  29. Hanganu J, Constantinescu A (2015) Land cover changes in Romania based on Corine Land Cover inventory 1990–2012. Romanian Journal of Geography 59(2): 111–116.Google Scholar
  30. Hosmer DW, Lemeshow S (1989) Applied logistic regression. John Wiley & Sons, Hoboken, NJ, USA. sp 307. Google Scholar
  31. Hosonuma N, Herold M, de Sy V, et al. (2012) An assessment of deforestation and forest degradation drivers in developing countries. Environmental Research Letters 7(4): 044009. CrossRefGoogle Scholar
  32. Iojā CI, Pātroescu M, Rozylowicz L, et al. (2010) The efficacy of Romania’s protected areas network in conserving biodiversity. Biological Conservation 143(11): 2468–2476. CrossRefGoogle Scholar
  33. Ioras F, Abrudan IV, Dautbasic M, et al. (2009) Conservation gains through HCVF assessments in Bosnia-Herzegovina and Romania. Biodiversity and Conservation 18: 3395–3406. CrossRefGoogle Scholar
  34. Irimie DL, Essmann HF (2009) Forest property rights in the frame of public policies and societal change. Forest Policy and Economics 11(2): 95–101. CrossRefGoogle Scholar
  35. Jennes J (2006) Topographic Position Index. tpi jen.avx, extension for ArcView 3.x; v.1.3a. Jenness Enterprises. Scholar
  36. Kaim D, Radeloff VC, Szwagrzyk M, et al. (2018) Long-term changes of the Wildland–Urban interface in the polish carpathians. ISPRS International Journal of Geo-Information 7(4): 137. CrossRefGoogle Scholar
  37. Kaimowitz D, Mendez P, Puntodewo A, et al. (2002) Spatial regression analysis of deforestation in Santa Cruz. Bolivia. In: Wood CH, Porro R (eds.), Land Use and Deforestation in the Amazon. University of Florida Press. pp 41–65.Google Scholar
  38. Kissling-Näf I, Bisang K (2001) Rethinking recent changes of forest regimes in Europe through property-rights theory and policy analysis. Forest Policy and Economics 3(3–4): 99–111. CrossRefGoogle Scholar
  39. Knorn J, Rabe A, Radeloff VC, et al. (2009) Land cover mapping of large areas using chain classification of neighboring Landsat satellite images. Remote Sensing of Environment 113(5): 957–964. CrossRefGoogle Scholar
  40. Knorn J, Kuemmerle T, Radeloff VC, et al. (2012a) Forest restitution and protected area effectiveness in post-socialist Romania. Biological Conservation 146(1): 204–212. CrossRefGoogle Scholar
  41. Knorn J, Kuemmerle T, Radeloff VC, et al. (2012b) Continued loss of temperate old-growth forests in the Romanian Carpathians despite an increasing protected area network. Environmental Conservation 40(2):182–193. CrossRefGoogle Scholar
  42. Kozak J, Estreguil C, Troll M (2007) Forest cover changes in the northern Carpathians in the 20th century: a slow transition. Journal of Land Use Science 2(2): 127–146. CrossRefGoogle Scholar
  43. Kozak J, Estreguil C, Ostapowicz K (2008) European forest cover mapping with high resolution satellite data: The Carpathians case study. International Journal of Applied Earth Observation and Geoinformation 10(1): 44–55. CrossRefGoogle Scholar
  44. Körner C, Ohsawa M, Spehn E, et al. (2005). Mountain systems. In: Hassan R, et al. (eds.), Ecosystem and human well-being: current state and trends: findings of the Conditions and Trends working group. Millennium Ecosystem Assessment 1. Washington, DC (USA) Island Press. pp 681–716.Google Scholar
  45. Kucsicsa G, Popovici EA, Bălteanu D, et al. (2019) Future land use/cover changes in Romania: regional simulations based on CLUE-S model and CORINE land cover database. Landscape and Ecological Engineering 15(1): 75–90. CrossRefGoogle Scholar
  46. Kuemmerle T, Hostert P, Radeloff VC, et al. (2007) Post-socialist forest disturbance in the carpathian border region of Poland, Slovakia, and Ukraine. Ecological Applications 17(5): 1279–1295. CrossRefGoogle Scholar
  47. Kuemmerle T, Müller D, Griffiths P, et al. (2009) Land use change in Southern Romania after the collapse of socialism. Regional Environmental Change 9(1): 1–12. CrossRefGoogle Scholar
  48. Kuemmerle T, Chaskovskyy O, Knorn J, et al. (2009) Forest cover change and illegal logging in the Ukrainian Carpathians in the transition period from 1988 to 2007. Remote Sensing of Environment 113(6): 1194–1207. CrossRefGoogle Scholar
  49. Kumar R, Nandy S, Agarwal R, et al. (2014) Forest cover dynamics analysis and prediction modeling using logistic regression model. Ecological Indicators 45: 444–455. CrossRefGoogle Scholar
  50. Kupková L, Potůčková M, Lhotáková Z, et al. (2018) Forest cover and disturbance changes, and their driving forces: A case study in the Ore Mountains, Czechia, heavily affected by anthropogenic acidic pollution in the second half of the 20th century. Environmental Research Letters 13(9): 095008. CrossRefGoogle Scholar
  51. Lambin EF (1994) Modelling deforestation processes, a review. EUR 15744 EN, TREES series B: Research Report No. 1. Joint Research Centre, Institute for Remote Sensing Applications, European Space Agency, Luxembourg, Office for Official Publications of the European Community. p 128.Google Scholar
  52. Laurance WF, Albernaz AKM, Schroth G, et al. (2002) Predictors of deforestation in the Brazilian amazon. Journal of Biogeography 29(5–6): 737–748. CrossRefGoogle Scholar
  53. Lerman Z, Csaki C, Feder G (2004) Evolving farm structures and land-use patterns in former socialist countries. Quarterly Journal of International Agriculture 43(4): 309–335.Google Scholar
  54. Liebetrau AM (1983) Measures of Association. Quantitative Applications in the Social Sciences 32. SAGE Publications, Newbury Park, CA.Google Scholar
  55. Linkie M, Rood E, Smith RJ (2010) Modelling the effectiveness of enforcement strategies for avoiding tropical deforestation in Kerinci Seblat National Park, Sumatra. Biodiversity and Conservation 19(4): 973–984. CrossRefGoogle Scholar
  56. Loza AV (2004) Spatial logistic model for tropical forest conversion: a case study of Carrasco province (1986–2002), Bolivia. (M.Sc. Thesis). International Institute for Geoinformation Science and Earth Observation, Enschede, The Netherlands. p 74.Google Scholar
  57. Ludeke AK, Maggio RC, Reid LM (1990) An analysis of anthropogenic deforestation using logistic regression and GIS. Journal of Environmental Management 31(3): 247–259. CrossRefGoogle Scholar
  58. Malek Ž, Zumpano V, Hussin H (2018) Forest management and future changes to ecosystem services in the Romanian Carpathians. Environment, Development and Sustainability 20(3):1275–1291. CrossRefGoogle Scholar
  59. Mantescu L, Vasile M (2009) Property reforms in rural Romania and community-based forests. Romanian Sociology 7(2): 95–113.Google Scholar
  60. Mas JF, Puig H (2001) Modalities of deforestation in south-western Campeche State, Mexico. Canadian Journal of Forest Research 31(7): 1280–1288. (In French). CrossRefGoogle Scholar
  61. Mas JF, Puig H, Palacio JL, et al. (2004) Modelling deforestation using GIS and artificial neural networks. Environmental Modelling & Software 19(5): 461–471. CrossRefGoogle Scholar
  62. McGarigal K, Marks BJ (1995) FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. Gen Tech Rep PNW-GTR-351. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. p 122.CrossRefGoogle Scholar
  63. McCullagh P, Nelder JA (1989) Generalized Linear Models. New York: Chapman and Hall. p 81.CrossRefGoogle Scholar
  64. Mertens B, Lambin EF (1997) Spatial modeling of tropical deforestation in south-ern Cameroon: spatial disaggregation of diverse deforestation processes. Applied Geography 17(2): 143–162. CrossRefGoogle Scholar
  65. Michalski F, Peresi FC, Lake IR (2008) Deforestation dynamics in a fragmented region of southern Amazonia: evaluation and future scenarios. Environmental Conservation 35(2): 93–103. CrossRefGoogle Scholar
  66. Mihai B, Sāvulescu I, Rujoiu-Mare M, Nistor C (2017) Recent forest cover changes (2002–2015) in the Southern Carpathians: A case study of the Iezer Mountains, Romania. Science of Total Environment 599–600: 2166–2174. CrossRefGoogle Scholar
  67. Minetos D, Polyzos S (2010) Deforestation processes in Greece: A spatial analysis by using an ordinal regression model. Forest Policy and Economics 12(6): 457–472. CrossRefGoogle Scholar
  68. Mon MS, Mizoue N, Htun NZ, et al. (2012) Factors affecting deforestation and forest degradation in selectively logged production forest: A case study in Myanmar. Forest Ecology and Management 267: 190–198. CrossRefGoogle Scholar
  69. Munteanu C, Kuemmerle T, Boltiziar M, et al. (2014) Forest and agricultural land change in the Carpathian region—A meta-analysis of long-term patterns and drivers of change. Land Use Policy 38: 685–697. CrossRefGoogle Scholar
  70. Munteanu C, Kuemmerle T, Keuler NS, et al. (2015) Legacies of 19th century land use shape contemporary forest cover. Global Environmental Change 34: 83–94. CrossRefGoogle Scholar
  71. Nagelkerke NJD (1991) A note on a general definition of the coefficient of determination. Biometrika 78(3): 691–692. CrossRefGoogle Scholar
  72. Nandy S, Kushwaha SPS, Mukhopadhyay S (2007) Monitoring the Chilla-Motichur wildlife corridor using geospatial tools. Journal for Nature Conservation 15(4): 237–244. CrossRefGoogle Scholar
  73. Nichiforel L, Schanz H (2011) Property rights distribution and entrepreneurial rent-seeking in Romanian forestry: a perspective of private forest owners. European Journal of Forest Research 130(3): 369–381. CrossRefGoogle Scholar
  74. Pahari K, Murai S (1999) Modelling for prediction of global deforestation based on the growth of human population. ISPRS Journal of Photogrammetry and Remote Sensing 54(5–6): 317–324. CrossRefGoogle Scholar
  75. Petritor AI (2015) Using CORINE data to look at deforestation in Romania: distribution & possible consequences. Urbanism. Arhitectura. Constructii 6(1): 83–90.Google Scholar
  76. Pontius GR Jr, Schneider CL (2001), Land -covor change model validation by an ROC method for the Ipswich watershed, Massachusetts, USA. Agriculture, Ecosystems and Environment 85: 239–248. CrossRefGoogle Scholar
  77. Popovici EA, Bălteanu D, Kucsicsa GH (2013) Assessment of changes in Land-Use and Land-Cover pattern in Romania using Corine Land Cover database. Carpathian Journal of Earth and Environmental Sciences 8(4): 195–208.Google Scholar
  78. Popovici EA, Kucsicsa G, Bălteanu D, et al. (2018) Past and future land use/cover flows related to agricultural lands in Romania. An assessment using CLUE-S Model and CORINE Land Cover Database. Carpathian Journal of Earth and Environmental Sciences 13(2): 613–628. CrossRefGoogle Scholar
  79. Rempel RS, Kaukinen D, Carr AP (2012) Patch Analyst and Patch Grid. Ontario Ministry of Natural Resources. Centre for Northern Forest Ecosystem Research, Thunder Bay, Ontario.Google Scholar
  80. Rozylowicz L, Popescu VD, Pătroescu M, et al. (2011) The potential of large carnivores as conservation surrogates in the Romanian Carpathians. Biodiversity and Conservation 20(3): 561–579. CrossRefGoogle Scholar
  81. Salvatori V, Okarma H, Ionescu O, et al. (2002) Hunting legislation in the Carpathian Mountains: implications for the conservation and management of large carnivores. Wildlife Biology 8(1): 3–10. CrossRefGoogle Scholar
  82. Šamonil P, Antolík L, Svoboda M, et al. (2009) Dynamics of windthrow events in a natural fir-beech forest in the Carpathian mountains. Forest Ecology and Management 257(3): 1148–1156. CrossRefGoogle Scholar
  83. Săvulescu I, Mihai B (2011) Geographic information system (GIS) application for windthrow mapping and management in Iezer Mountains, Southern Carpathians. Journal of Forestry Research 23(2): 175–184. Google Scholar
  84. Shandra O, Weisberg P, Martazinova V (2013) Influences of climate and land use history on forest and timberline dynamics in the Carpathian Mountains during the twentieth century. In: Kozak J, et al. (eds.), The Carpathians: Integrating Nature and Society Towards Sustainability. Springer, Berlin Heidelberg. pp 209–223. CrossRefGoogle Scholar
  85. Schelhaas MJ, Nabuurs GJ, Schuck A (2003) Natural disturbances in the European forests in the 19th and 20th centuries. Global Change Biology 9(11): 1620–1633. CrossRefGoogle Scholar
  86. Siles NJS (2009) Spatial Modelling and prediction of tropical forest conversion in the Isiboro Secure National Park and Indigenous Territory (TIPNIS), Bolivia. (M.Sc. Thesis). International Institute for Geoinformation Science and Earth Observation, Enschede, The Netherlands.Google Scholar
  87. Skaloš J, Weber M, Lipský Z, et al. (2011) Using old military survey maps and orthophotograph maps to analyse long-term land cover changes–Case study (Czech Republic). Applied Geography 31(2): 426–438. CrossRefGoogle Scholar
  88. Skaloš J, Engstová B, Trpáková I, et al. (2012) Long-term changes in forest cover 1780–2007 in central Bohemia, Czech Republic. European Journal of Forest Research 131(3): 871–884. CrossRefGoogle Scholar
  89. Sobala M, Rahmonov O, Myga-Piatek U (2017) Historical and contemporary forest ecosystem changes in the Beskid Mountains (southern Poland) between 1848 and 2014. IForest - Biogeosciences and Forestry 10(6): 939–947. CrossRefGoogle Scholar
  90. Sun J, Southworth J (2013) Remote sensing-based fractal analysis and scale dependence associated with forest fragmentation in an amazon Tri-National frontier. Remote Sensing 5(2): 454–472. CrossRefGoogle Scholar
  91. Sitko I, Troll M (2008) Timberline changes in relation to summer farming in the Western Chornohora (Ukrainian carpathians). Mountain Research and Development 28(3/4): 263–271. CrossRefGoogle Scholar
  92. Szymura TH, Murak S, Szymura M, et al. (2018) Changes in forest cover in Sudety Mountains during the last 250 years: patterns, drivers, and landscape-scale implications for nature conservation. Acta Societatis Botanicorum Poloniae 87(1).
  93. Turnock D (2002) Ecoregion-based conservation in the Carpathians and the land-use implications. Land Use Policy 19(1):47–63. CrossRefGoogle Scholar
  94. Van Maanen E, Predoiu G, Klaver R, et al. (2006) Safeguarding the Romanian Carpathian Ecological Network. A vision for large carnivores and biodiversity in Eastern Europe. A&W Ecological Consultants, Veenwouden, The Netherlands. ICAS Wildlife Unit, Brasov, Romania.Google Scholar
  95. Vanonckelen S, van Rompaey A (2015) Spatiotemporal analysis of the controlling factors of forest cover change in the Romanian carpathian mountains. Mountain Research and Development 35(4): 338–350. CrossRefGoogle Scholar
  96. Vanonckelen S, Lhermitte S, van Rompaey A (2015) The effect of atmospheric and topographic correction on pixel-based image composites: Improved forest cover detection in mountain environments. International Journal of Applied Earth Observation and Geoinformation 35: 320–328. CrossRefGoogle Scholar
  97. Weisberg PJ, Shandra O, Becker ME (2013) Landscape influences on recent timberline shifts in the Carpathian Mountains: abiotic influences modulate effects of land-use change. Arctic, Antarctic, and Alpine Research 45(3): 404–414. CrossRefGoogle Scholar
  98. Weiss A (2001) Topographic Position and Landforms Analysis. Poster presentation. ESRI User Conference, San Diego, CA.Google Scholar
  99. Wilson K, Newton A, Echeverría C, et al. (2005) A vulnerability analysis of the temperate forests of south central Chile. Biological Conservation 122(1): 9–21. CrossRefGoogle Scholar

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© Science Press, Institute of Mountain Hazards and Environment, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of GeographyRomanian AcademyBucharestRomania

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