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A small-scale landslide susceptibility assessment for the territory of Western Carpathians

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Abstract

This study presented herein compares the bivariate and multivariate landslide susceptibility mapping methods and presents the landslide susceptibility map of the territory of Western Carpathians in small scale. This study also describes pioneer work for the territory of Western Carpathians, overreaching state borders, using verified sophisticated statistical methods. In the susceptibility mapping, digital elevation model was first constructed using a GIS software, and parameter maps affecting the slope stability such as geology, seismicity, precipitation, topographical elevation, slope angle, slope aspect and land cover were considered. In the last stage of the analyses, landslide susceptibility maps were produced using bivariate and multivariate analyses, and they were then compared by means of their validations. The validation of the bivariate analysis data was performed using the results of bivariate analysis for landslide areas of Slovakia containing five classes of susceptibility in scale 1:500,000. The validation area is the area of Western Carpathians within Slovakia. Eighty-two per cent of area does not differ in more than one class. The validation of the multivariate analysis data was performed using the results from the Kysuce region in the northern part of Slovakia in scale 1:10,000. The raster calculator was used to express the difference between each pair of pixels within these two layers. Seventy-seven per cent of the pixels do not differ in more than 25 %, 94 % of the pixels do not differ in more than 50 %. The maximal possible difference is 100 % (one pixel with value 0 and other with value 1, or vice versa). Receiver operating characteristic analysis was also performed, the area under curve value for bivariate model was calculated to be 0.735, while it was 0.823 for multivariate. The results of the validation can be considered as satisfactory.

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References

  • Arora MK, Gupta ASD, Gupta RP (2004) An artificial neural network approach for landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas. Int J Remote Sens 25(3):559–572

    Article  Google Scholar 

  • Atkinson PM, Massari R (1998) Generalised linear modelling of susceptibility to landsliding in the Central Appenines, Italy. Comput Geosci 24(4):373–385

    Article  Google Scholar 

  • Ayala FJ (1987) Introducción a los riesgos geológicos (Introduction to geological risk). In: Ayala FJ (ed) Riesgos Geológicos (geological risks), IGME (Instituto Geologico y Minero de Espana—Spain Institute of Geology and Mining). Serie Geología Ambiental, Madrid, pp 3–19

    Google Scholar 

  • Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda–Yahiko Mountains, central Japan. Geomorphology 65:15–31

    Article  Google Scholar 

  • Ayalew L, Yamagishi H, Marui H, Kanno T (2005) Landslides in Sado Island of Japan Part II. GIS-based susceptibility mapping with comparisons of results from two methods and validations. Eng Geol 81:432–445

    Article  Google Scholar 

  • Baeza C (1994) Evaluación de las condiciones de rotura y la movilidad de los deslizamientos superficiales mediante el uso de técnicas de análisis multivariante (Evaluation of the failure conditions and mobility by using multivariate analysis in superficial media.). PhD thesis, University Politechnique Catalunya (in Spanish)

  • Baeza C, Corominas J (2001) Assessment of shallow landslide susceptibility by means of multivariate statistical techniques. Earth Surf Proc Landf 26:1251–1263

    Article  Google Scholar 

  • Bednarik M, Clerici A, Tellini C, Vescovi P (2005) Using GIS GRASS in evaluation of landslide susceptibility in Termina valley in the Northern Appennines (Italy). In: Moser M (ed) Proceedings of the conference on engineering geology: forum for young engineering geologists. DGGT Erlangen-Nürnberg, Fridrich–Alexander–University of Erlangen, Nürnberg, April 6th to 9th 2005, pp 19–24

  • Bednarik M, Liščák P (2009) Landslide susceptibility assessment in Slovakia. Miner Slovaca 42:193–204

    Google Scholar 

  • Bednarik M, Pauditš P (2010) Different ways of landslide geometry interpretation in a process of statistical landslide susceptibility and hazard assessment: Horná Súča (western Slovakia) case study. Environ Earth Sci 61(4):733–739

    Article  Google Scholar 

  • Bednarik M, Magulová B, Matys M, Marschalko M (2010) Landslide susceptibility assessment of the Kraľovany–Liptovský Mikuláš railway case study. Phys Chem Earth 35:3–5

    Google Scholar 

  • Bednarik M (2011) Landslide hazard and risk assessment based on statistical methods. Inaugural dissertation—manuscript. Prif UK, Bratislava

    Google Scholar 

  • Bednarik M, Yilmaz I, Marschalko M (2012) Landslide hazard and risk assessment: a case study from the Hlohovec-Sered landslide area in south-west Slovakia. Nat Hazards. doi:10.1007/s11069-012-0257-7

    Google Scholar 

  • Brabb EE, Pampeyan EH, Bonilla M (1972) Landslide susceptibility in the San Mateo County, California, scale 1:62,500. USGS Miscellaneous Field Studies Map, MF344

  • Bui DT, Pradhan B, Lofman O, Revhaug I, Dick OB (2012) Spatial prediction of landslide hazards in Hoa Binh province (Vietnam): a comparative assessment of the efficacy of evidential belief functions and fuzzy logic models. Catena 96:28–40

    Article  Google Scholar 

  • Carrara A, Cardinalli M, Detti R, Guzzetti F, Pasqui V, Reichenbach P (1991) GIS techniques and statistical models in evaluating landslide hazards. Earth Surf Proc Landf 16:427–445

    Article  Google Scholar 

  • Chacon J, Irigaray C, Fenandez T (1992) Metodologia para la cartografia regianal de movientos de ladera y riesgos asociados mediante un Sistema de Informacions Geografica (Methodology in mapping of regional landslides by means of Geographical Information System). In: Corominas J, Alonso E (eds) III Simposio Nacional sobre Taludes y laderas Inesstables, La Corruna, Spain, I, pp 121–133

  • Chacón J, Irigaray C, Fernández T (1994) Large to middle scale landslide inventory, analysis and mapping with modeling and assessment of derived susceptibility, hazards and risks in a GIS. In: Proceedings of 7th IAEG Congress, Balkema, Rotterdam, pp 4669–4678

  • Chacón J, Irigaray C, Fernández T (1996) From the inventory to the risk analysis: improvements to a large scale GIS method. In: Chacón J, Irigaray C, Fernández T (eds) Proceedings of 8th international conference and field workshop on landslides, Balkema, pp 335–342

  • Chau KT, Chan JE (2005) Regional bias of landslide data in generating susceptibility maps using logistic regression Case of Hong Kong Island. Landslides 2:280–290

    Article  Google Scholar 

  • Chen H, Dadson S, Chi YG (2006) Recent rainfall-induced landslides and debris flow in northern Taiwan. Geomorphology 77:112–125

    Article  Google Scholar 

  • Chung CF, Fabbri AG, van Westen CJ (1995) Multivariate regression analiysis for landslide hazard zonalition. In: Carrara A, Guzetti F (eds) Geographical informations systems in assessing natural hazards. Kluwer, Dordrecht

    Google Scholar 

  • Chung CF, Fabbri AG (1999) Probabilistic prediction models for landslide hazard mapping. Photogramm Eng Remote Sens 65(12):1389–1399

    Google Scholar 

  • Clerici A (2002) A GRASS GIS based shell script for landslide susceptibility zonation by the conditional analysis method. In: Ciolli M, Zatelli P (eds) Proceedings of the open source GIS GRASS users conference, Trento, Italy

  • Clerici A, Perego S, Tellini C, Vescovi P (2006) A GIS-based automated procedure for landslide susceptibility mapping by the conditional analysis method: the Baganza valley case study (Italian Northern Appennines). Environ Geol 50(7):941–961

    Article  Google Scholar 

  • Conoscenti C, Di Maggio C, Rotigliano E (2008) GIS analysis to assess landslide susceptibility in a fluvial basin of NW Sicily (Italy). Geomorphology 94:325–339

    Article  Google Scholar 

  • Constantin M, Bednarik M, Jurchescu MC, Vlaicu M (2011) Landslide susceptibility assessment using the bivariate statistical analysis and the index of entropy in the Sibiciu Basin (Romania). Environ Earth Sci 63(2):397–406

    Article  Google Scholar 

  • Corominas J (1987) Criterios para la confeccion de mapes de peligrosidad de movimentos de ladera (Criteria for preparation of landslide hazard maps). In: Ayala FJ (ed) Riesgos Geologicos, IGME (Instituto Geologico y Minero de Espana—Spain Institute of Geology and Mining). Serie Geologia Ambiental, Madrid, pp 193–201

    Google Scholar 

  • Corominas J, Moya J (1996) Historical landslide in the Eastern Pyrenees and their relation to rainy event. In: Crosta G, Frattini P (eds) Landslides. Chacon, Irigary-Fern’andez, Balkema, AA, Rotterdam, pp 125–132

  • Dai FC, Lee CF, Li J, Xu ZW (2001) Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong. Environ Geol 40(3):381–391

    Article  Google Scholar 

  • Dai FC, Lee CF (2003) A spatiotemporal probabilistic modelling of storm-induced shallow landsliding using aerial photographs and logistic regression. Earth Surf Proc Landf 28:527–545

    Article  Google Scholar 

  • DeGraff J, Romesburg H (1980) Regional landslide-susceptibility assessment for wildland management: a matrix approach. In: Coates D, Vitek J (eds) Thresholds in geomorphology. George Allen and Unwin, London, pp 401–414

    Google Scholar 

  • Domínguez-Cuesta MJ, Jiménez-Sánchez M, Berrezueta E (2007) Landslides in the Central Coalfield (Cantabrian Mountains, NW Spain): geomorphological features, conditioning factors and methodological implications in susceptibility assessment. Geomorphology 89:358–369

    Article  Google Scholar 

  • Donati L, Turrini MC (2002) An objective method to rank the importance of the factors predisposing to landslides with the GIS methodology: application to an area of the Apennines (Valnerina, Perugia, Italy). Eng Geol 63:277–289

    Article  Google Scholar 

  • Embleton C, Embleton-Hamann C (1997) Geomorphological hazards of Europe. Elsevier, Amsterdam

    Google Scholar 

  • Ercanoglu M, Kasmer O, Temiz N (2008) Adaptation and comparison of expert opinion to analytical hierarchy process for landslide susceptibility mapping. Bull Eng Geol Environ 67:565–578

    Article  Google Scholar 

  • Fülöp J, Rónai A (1984) Geological map of Hungary 1:500,000. Edited by the Hungarian Geological Institute, Budapest

    Google Scholar 

  • Fernández T, Irigaray C, Hamdouni RE, Chacón J (2003) Methodology for landslide susceptibility mapping by means of a GIS, application to the contraviesa area (Granada, Spain). Nat Hazards 30:297–308

    Article  Google Scholar 

  • Frattini P, Crosta G, Carrara A (2010) Techniques for evaluating the performance of landslide susceptibility models. Eng Geol 111:62–72

    Article  Google Scholar 

  • Giardini D, Grünthal G, Shedlock K, Zhang P (1999) The GSHAP global seismic hazard map. Ann Geophys 42(6):1225–1228

    Google Scholar 

  • Gokceoglu C, Aksoy H (1996) Landslide susceptibility mapping of the slopes in the residual soils of the Mengen region (Turkey) by deterministic stability analyses and image processing techniques. Eng Geol 44(1–4):147–161

    Article  Google Scholar 

  • Gomez H, Kavzoglu T (2005) Assessment of shallow landslide susceptibility using artificial neural networks in Jabonosa River Basin, Venezuela. Eng Geol 78(1–2):11–27

    Article  Google Scholar 

  • Greco R, Sorriso-Valvo M, Catalano E (2006) Logistic regression analysis in the evaluation of mass movements susceptibility: the Aspromonte case study, Calabria, Italy. Eng Geol 89:47–66

    Article  Google Scholar 

  • Hack R, Alkema D, Kruse GAM, Leenders N, Luzi L (2007) Influence of earthquakes on the stability of slopes. Eng Geol 91(1):4–15

    Article  Google Scholar 

  • Haneberg WC, Gocke AO (1994) Rapid water level fluctuations in a thin colluvium landslide west of Cincinnati, Ohio. US Geol Surv Bull 2059 C:1–16

    Google Scholar 

  • Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978

    Article  Google Scholar 

  • Hrašna M (1986) Mapy inžinierskogeologického rajónovania pre účely urbanizácie. In: Zborník referátov z vedeckej konferencie Progresívne smery v inžinierskogeologickom výskume. PRIF UK Bratislava, Katedra inžinierskej geológie, pp 68–82

  • International Association of Engineering Geology (IAEG) (1976) Engineering geological maps: a guide to their preparation. UNESCO Press, Paris, p 79

    Google Scholar 

  • Irigaray C (1995) Movimientos de ladera: inventoria, analisis y cartografaa de susceptibilidad mediante un Sistema de Informacion Geografica. Aplicacion a las zonas de Colmenar (Ma), Rute (Co) y Montefrio (Gr) (Landslides: inventory, susceptibility analysis and mapping by means of a geographical information system. Application to the Colmenar (Malaga), Rute (Cordoba) and Montefrio (Granada) sectors). PhD thesis, University Granada (in Spanish)

  • Jade S, Sarkar S (1993) Statistical models for slope instability classification. Eng Geol 36:91–98

    Article  Google Scholar 

  • Juang CH, Lee DH, Sheu C (1992) Mapping slope failure potential using fuzzy sets. J Geotech Eng ASCE 118:475–494

    Article  Google Scholar 

  • Kanungo DP, Arora MK, Sarkar S, Gupta RP (2006) A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas. Eng Geol 85(3–4):347–366

    Article  Google Scholar 

  • Katzensteiner H, Bell R, Petschko H, Glade T (2012) The relationship between extreme precipitation events and landslides distributions in 2009 in Lower Austria. VIII. EGU General Assembly 2012, Vienna, Austria, 22–27 April, Geophysical Research Abstracts, 14, ID: 10618

  • Keefer DK (1994) The importance of earthquake-induced landslides to long-term slope erosion and slope-failure hazards in seismically active regions. Geomorphology 10:265–284

    Article  Google Scholar 

  • Keefer DK (2000) Statistical analysis of an earthquake-induced landslide distribution—the 1989 Loma Prieta, California event. Eng Geol 58(3–4):231–249

    Article  Google Scholar 

  • Klimaszewski M (1985) Geomorfologia 1:30,000. In: Atlas Tatrzańskiego parku narodowego. TPN, Polskie Towarzystwo Przyjaciół Nauk o Ziemi, Kraków, p 9

  • Lee S, Min K (2001) Statistical analysis of landslide susceptibility at Yongin, Korea. Environ Geol 40:1095–1113

    Article  Google Scholar 

  • Lee S, Ryu JH, Min K, Won JS (2003a) Landslide susceptibility analysis using GIS and artificial neural network. Earth Surf Proc Landf 27:1361–1376

    Article  Google Scholar 

  • Lee S, Ryu JH, Lee MJ, Won JS (2003b) Landslide susceptibility analysis using artificial neural network at Boun, Korea. Environ Geol 44:820–833

    Article  Google Scholar 

  • Lee S, Ryu JH, Won JS, Park HJ (2004) Determination and application of the weights for landslide susceptibility mapping: using an artificial neural network. Eng Geol 71:289–302

    Article  Google Scholar 

  • Lee S (2005) Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. Int J Remote Sens 26(7):1477–1491

    Article  Google Scholar 

  • Lexa J, Bezák V, Elečko M, Eliáš M, Konečný V, Less Gy, Mandl GW, Mello J, Pálenský P, Pelikán P, Polák M, Potfaj M, Radócz Gy, Rylko W, Schnabel GW, Stráník Z, Vass D, Vozár J, Zelenka T, Biely A, Čtyroký P, Kaličiak M, Kohút M, Kovács S, Mackiv B, Maglay J, Nemčok J, Nowotny A, Pentelényi L, Rakús M, Vozárová A (2000) Geological map of Western Carpathians and adjacent areas. Geological Survey of Slovak Republic, Bratislava

  • Liščák P, Pauditš P, Petro Ľ, Iglárová Ľ, Ondrejka P, Dananaj I, Brček M, Baráth I, Vlačiky M, Németh Z, Záhorová Ľ, Antalík M, Repčiak M, Drotár D (2010) Registration and evaluation of newly evolved slope failures in Prešov and Košice Regions in 2010. Miner Slovaca 42:393–406

    Google Scholar 

  • Lui Y, Guo HC, Zou R, Wang LJ (2006) Neural network modelling for regional hazard assessment of debris flow in Lake Qionghai Watershed, China. Environ Geol 49:968–976

    Article  Google Scholar 

  • Malamud BD, Turcotte DL, Guzzetti F, Reichenbach P (2012) Landslides and earthquakes. In: American geophysical union, fall meeting 2012, abstract #H12D-0957

  • Marjanović M (2009) Landslide susceptibility modelling: a case study on Fruška gora Mountain, Serbia. Geomorphol Slovaca et Bohemica 9(1):29–42

    Google Scholar 

  • Melchiorre C, Matteucci M, Azzoni A, Zanchi A (2008) Artificial neural networks and cluster analysis in landslide susceptibility zonation. Geomorphology 94:379–400

    Article  Google Scholar 

  • Minár J, Bielik M, Kováč M, Plašienka D, Barka I, Stankoviansky M, Zeyen H (2011) New morphostructural subdivision of the Western Carpathians: an approach integrating geodynamics into targeted morphometric analysis. Tectonophysics 502(1–2):158–174

    Article  Google Scholar 

  • Mukherjee S, Joshi PK, Mukherjee S, Ghosh A, Garg RD, Mukhopadhyay A (2013) Evaluation of vertical accuracy of open source digital elevation model (DEM). Int J Appl Earth Obs Geoinf 21:205–217

    Article  Google Scholar 

  • Nandi A, Shakoor A (2009) A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses. Eng Geol 110:11–20

    Article  Google Scholar 

  • Nefeslioglu HA, Gokceoglu C, Sonmez H (2008) An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps. Eng Geol 97(3–4):171–191

    Article  Google Scholar 

  • Nemčok A, Pašek J, Rybář J (1974) Slope movements and their classifications. Sborníkgeologických Věd 11(1):77–93

    Google Scholar 

  • Nemčok A (1982) Landslides in Slovak Carpathians. Landslide hazard in the Polish flysch Carpathians. Stud Geomorphol Carpatho-Balcanica 41:61–76

    Google Scholar 

  • Neuhäuser B, Damm B, Terhorst B (2012) GIS-based assessment of landslide susceptibility on the base of the weights-of-evidence model. Landslides 9:511–528

    Article  Google Scholar 

  • Oh HJ, Pradhan B (2011) Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area. Comput Geosci 37(9):1264–1276

    Article  Google Scholar 

  • Ohlmacher CG, Davis CJ (2003) Using multiple regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Eng Geol 69:331–343

    Article  Google Scholar 

  • Pachauri AK, Pant M (1992) Landslide hazard mapping based on geological attributes. Eng Geol 32(1–2):81–100

    Article  Google Scholar 

  • Pistocchi A, Luzi L, Napolitano P (2002) The use of predictive modeling techniques for optimal exploitation of spatial databases: a case study in landslide hazard mapping with expert system-like methods. Environ Geol 41:765–775

    Article  Google Scholar 

  • Plašienka D (2002) Origin and growth of the Western Carpathian orogenetic wedge during the Mesozoic. Geologica Carpathica special issues, 53. In: Proceedings of theXVII Congress of Carpathian-Balkan Geological Association Bratislava, September 1st–4th 2002

  • Pradhan B (2011) Manifestation of an advanced fuzzy logic model coupled with Geo-information techniques to landslide susceptibility mapping and their comparison with logistic regression modelling. Environ Ecol Stat 18(3):471–493

    Article  Google Scholar 

  • Pradhan B, Sezer EA, Gokceoglu C, Buchroithner MF (2010) Landslide susceptibility mapping by neuro-fuzzy approach in a landslide-prone area (Cameron Highlands, Malaysia). IEEE Trans Geosci Remote Sens 48(12):4164–4177

    Article  Google Scholar 

  • Rączkowski W (2007) Landslide hazard in the Polish flysch Carpathians. Stud Geomorphol Carpatho Balc 41:61–75

    Google Scholar 

  • Saboya F Jr, Alves MG, Pinto WD (2006) Assessment of failure susceptibility of soil slopes using fuzzy logic. Eng Geol 86:211–224

    Article  Google Scholar 

  • Santacana N, Baeza B, Corominas J, Paz A, Marturia J (2003) A GIS-based multivariate statistical analysis for shallow landslide susceptibility mapping in la pobla de lillet area (Eastern Pyrenees, Spain). Nat Hazards 30:281–295

    Article  Google Scholar 

  • Scharek P (2005) Map of detected surface movements 1:500,000. In geological atlas of Hungary. Magyar Állami Földtani Intézet, Budapest

    Google Scholar 

  • Schenk V, Schenková Z, Kottnauer P, Guterch B, Labák P (2002) Seismic hazard in terms of peak ground acceleration on rock site 1:1,500,000. In Landscape Atlas of the Slovak republic. Ministry of Environment, Bratislava, p 276

    Google Scholar 

  • Schicker R, Moon V (2012) Comparison of bivariate and multivariate statistical approaches in landslide susceptibility mapping at a regional scale. Geomorphology 161:40–57

    Article  Google Scholar 

  • Smith K, Petley DN, (2009) Environmental hazards: assessing risk and reducing disaster, 5th edn. Routledge, London and Newyork

  • Soeters R, Van Westen CJ, (1996) Slope instability recognition, analysis, and zonation. In: Turner AK, Schuster RL (eds) Landslides: investigation and mitigation, National Research Council, Washington, DC, National Academy Press, Transportation Research Board Special Report 247, pp 129–177

  • Sterlacchini S, Ballabio C, Blahut J, Masetti M, Sorichetta A (2011) Spatial agreement of predicted patterns in landslide susceptibility maps. Geomorphology 125:51–61

    Article  Google Scholar 

  • Schenk V, Schenková Z (1998) CSN 73 0036, Amendment 2 ‘Seismic Loads of Buildings’. Czech technical code, ICS 91.080.00, 91.040.00. May 1998 Czech Normalisation Institute, Prague, 5 pp and 1 map

  • Süzen Ml, Doyuran V (2004) A comparison of the GIS based landslide susceptibility assessment methods: multivariate versus bivarite. Environ Geol 45(5):665–679

    Article  Google Scholar 

  • Šimeková J, Martinčeková T, Abrahám P, Gejdoš T, Grenčíková A, Grman D, Hrašna M, Jadroň D, Záthurecký A, Kotrčková E, Liščák P, Malgot J, Masný M, Mokrá M, Petro Ľ, Polaščinová E, Solčiansky R, Kopecký M, Žabková E, Wanieková D (2006) Atlas of slope stability maps of the Slovak Republic (1:50,000). Ingeo, Žilina

    Google Scholar 

  • Terlien MTJ (1996) Modeling spatial and temporal variations in rainfall-triggered landslides, vol 31. International Institute for Aerospace and Earth Sciences JTC, Enschede, p 254

  • Tsaparas I, Rahardjo H, Toll DG, Leong EC (2002) Controlling parameters for rainfall induced landslides. Comput Geotech 29:1–27

    Article  Google Scholar 

  • Turner K, Jayaprakash G (1996) Landslides: investigation and mitigation, introduction. In: Turner AK, Schuster RL (eds) Special report, vol 247., National Academic PressWashington, DC, pp 3–12

    Google Scholar 

  • Turrini MC, Visintainer P (1998) Proposal of a method to define areas of landslide hazard and application to an area of the Dolomites, Italy. Eng Geol 50(3–4):255–265

    Article  Google Scholar 

  • Van Asch TWJ, Sukmantalya IN (1993) The modeling of soil slip erosion in the upper Komering area, South Sumatra Province, Indonesia. Geografia Fisica E Dinamica Quaternaria 16:81–86

    Google Scholar 

  • Van Den Eeckhaut M, Vanwalleghem T, Poesen J, Govers G, Verstraeten G, Vandekerckhove L (2006) Prediction of landslide susceptibility using rare events logistic regression: a case-study in the Flemish Ardennes (Belgium). Geomorphology 76:392–410

    Article  Google Scholar 

  • Vlčko J, Wagner P, Rychlíková Z (1980) Evaluation of regional slope stability. Miner Slovaca 12(3):275–283

    Google Scholar 

  • Wang HB, Sassa K (2005) Comparative evaluation of landslide susceptibility in Minamata area, Japan. Environ Geol 47:956–966

    Article  Google Scholar 

  • Van Westen CJ, Rengers N, Terlien M, Soeters R (1997) Prediction of the occurrence of slope instability phenomenal through GIS-based hazard zonation. Geol Rundsch 86:404–414

    Article  Google Scholar 

  • Van Westen C, Rengers N, Soeters R (2003) Use of geomorphological information in indirect landslide susceptibility assessment. Nat Hazards 30:399–419

    Article  Google Scholar 

  • Van Westen C, Van Asch TWJ, Soeters R (2006) Landslide hazard and risk zonation—why is it still so difficult? Bull Eng Geol Environ 65:167–184

    Article  Google Scholar 

  • Varnes DJ (1984) Landslide hazard zonation—a review of principles and practise. UNESCO, Paris, p 63

    Google Scholar 

  • Yalcin A, Reis S, Aydinoglu AC, Yomralioglu T (2011) A GIS-based comparative study of frequency ratio, analytical hierarchy process, bivariate statistics and logistics regression methods for landslide susceptibility mapping in Trabzon, NE Turkey. Catena 85:274–287

    Article  Google Scholar 

  • Yilmaz I, Yildirim M (2006) Structural and geomorphological aspects of the Kat landslides (Tokat-Turkey), and susceptibility mapping by means of GIS. Environ Geol 50(4):461–472

    Article  Google Scholar 

  • Yilmaz I (2008) A case study from Koyulhisar (Sivas-Turkey) for landslide susceptibility mapping by artificial neural networks. Bull Eng Geol Environ 68(3):297–306

    Article  Google Scholar 

  • Yilmaz I (2009a) Landslide susceptibility using frequency ratio, logistic regression, artificial neural networks and their comparison: a case study from Kat landslides (Tokat-Turkey). Comput Geosci 35(6):1125–1138

    Article  Google Scholar 

  • Yilmaz I (2009b) A case study from Koyulhisar (Sivas-Turkey) for landslide susceptibility mapping by artificial neural networks. Bull Eng Geol Environ 68(3):297–306

    Article  Google Scholar 

  • Yilmaz I (2010a) The effect of the sampling strategies on the landslide susceptibility mapping by conditional probability (CP) and artificial neural networks (ANN). Environ Earth Sci 61(4):821–836

    Article  Google Scholar 

  • Yilmaz I (2010b) The effect of the sampling strategies on the landslide susceptibility mapping by conditional probability (CP) and artificial neural networks (ANN). Environ Earth Sci 60(3):505–519

    Article  Google Scholar 

  • Yilmaz I, Keskin I (2009) GIS based statistical and physical approaches to landslide susceptibility mapping (Sebinkarahisar, Turkey). Bull Eng Geol Environ 68(4):459–471

    Article  Google Scholar 

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Acknowledgments

This study was supported by the Slovak Research and Development Agency under contracts ESF-EC-0006-07, APVV-0625-11, APVV-0330-10 and VEGA 1/0910/11. Authors are grateful to experts from geological surveys and scientific institutions of Hungary, Czech republic, Poland and Austria, namely Péter Scharek, Petr Šeba, Wojciech Rączkowski, Michał Długosz, Arben Kociu and Klemens Grösel for help with collection of the data. Authors are deeply grateful to the Anonymous reviewers for their very constructive comments and suggestions which led to the improvement of the quality of the paper.

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  1. Department of Physical Geography and Geoecology, Faculty of Natural Sciences, Comenius University, Mlynská dolina, 842 15, Bratislava, Slovak Republic

    Juraj Holec, Marián Šabo & Jozef Minár

  2. Department of Engineering Geology, Faculty of Natural Sciences, Comenius University, Mlynská dolina, 842 15, Bratislava, Slovak Republic

    Martin Bednarik

  3. Department of Geological Engineering, Faculty of Engineering, Cumhuriyet University, 58140, Sivas, Turkey

    Isik Yilmaz

  4. Faculty of Mining and Geology, Institute of Geological Engineering, VŠB-Technical University of Ostrava, 17 Listopadu 15, 708 33, Ostrava, Czech Republic

    Marián Marschalko

Authors
  1. Juraj Holec
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  2. Martin Bednarik
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  3. Marián Šabo
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  4. Jozef Minár
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  5. Isik Yilmaz
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  6. Marián Marschalko
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Correspondence to Isik Yilmaz.

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Holec, J., Bednarik, M., Šabo, M. et al. A small-scale landslide susceptibility assessment for the territory of Western Carpathians. Nat Hazards 69, 1081–1107 (2013). https://doi.org/10.1007/s11069-013-0751-6

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  • DOI: https://doi.org/10.1007/s11069-013-0751-6

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