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

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.

[1]  Kaye M. Shedlock,et al.  The GSHAP Global Seismic Hazard Map , 2000 .

[2]  D. Keefer Statistical analysis of an earthquake-induced landslide distribution — the 1989 Loma Prieta, California event , 2000 .

[3]  C. Embleton,et al.  Geomorphological hazards of Europe , 1997 .

[4]  Biswajeet Pradhan,et al.  Spatial prediction of landslide hazards in Hoa Binh province (Vietnam): a comparative assessment of , 2012 .

[5]  A. Clerici,et al.  A GIS-based automated procedure for landslide susceptibility mapping by the Conditional Analysis method: the Baganza valley case study (Italian Northern Apennines) , 2006 .

[6]  Işık Yilmaz,et al.  A case study from Koyulhisar (Sivas-Turkey) for landslide susceptibility mapping by artificial neural networks , 2009 .

[7]  M. Turrini,et al.  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) , 2002 .

[8]  V. Doyuran,et al.  A comparison of the GIS based landslide susceptibility assessment methods: multivariate versus bivariate , 2004 .

[9]  Manoj Pant,et al.  Landslide hazard mapping based on geological attributes , 1992 .

[10]  R. Soeters,et al.  Use of Geomorphological Information in Indirect Landslide Susceptibility Assessment , 2003 .

[11]  J. Corominas,et al.  A GIS-Based Multivariate Statistical Analysis for Shallow Landslide Susceptibility Mapping in La Pobla de Lillet Area (Eastern Pyrenees, Spain) , 2003 .

[12]  M. K. Arora,et al.  An artificial neural network approach for landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas , 2004 .

[13]  Christian Conoscenti,et al.  GIS analysis to assess landslide susceptibility in a fluvial basin of NW Sicily (Italy) , 2008 .

[14]  H. A. Nefeslioglu,et al.  An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps , 2008 .

[15]  I. Yilmaz,et al.  GIS based statistical and physical approaches to landslide susceptibility mapping (Sebinkarahisar, Turkey) , 2009 .

[16]  R. Soeters,et al.  Slope instability recognition, analysis, and zonation , 1996 .

[17]  Jozef Minár,et al.  New morphostructural subdivision of the Western Carpathians: An approach integrating geodynamics into targeted morphometric analysis , 2011 .

[18]  Giovanni B. Crosta,et al.  Techniques for evaluating the performance of landslide susceptibility models , 2010 .

[19]  P. Atkinson,et al.  Generalised linear modelling of susceptibility to landsliding in the Central Apennines, Italy , 1998 .

[20]  J. Corominas,et al.  Assessment of shallow landslide susceptibility by means of multivariate statistical techniques , 2001 .

[21]  Vicki G. Moon,et al.  Comparison of bivariate and multivariate statistical approaches in landslide susceptibility mapping at a regional scale , 2012 .

[22]  H. Wang,et al.  Comparative evaluation of landslide susceptibility in Minamata area, Japan , 2005 .

[23]  C. Chung,et al.  Probabilistic prediction models for landslide hazard mapping , 1999 .

[24]  A Keith Turner,et al.  LANDSLIDES: INVESTIGATION AND MITIGATION. CHAPTER 1 - INTRODUCTION , 1996 .

[25]  L. Luzi,et al.  The use of predictive modeling techniques for optimal exploitation of spatial databases: a case study in landslide hazard mapping with expert system-like methods , 2002 .

[26]  L. Ayalew,et al.  The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan , 2005 .

[27]  M. Turrini,et al.  Proposal of a method to define areas of landslide hazard and application to an area of the Dolomites, Italy , 1998 .

[28]  Simon Dadson,et al.  Recent rainfall-induced landslides and debris flow in northern Taiwan , 2006 .

[29]  Marian Marschalko,et al.  Landslide hazard and risk assessment: a case study from the Hlohovec–Sered’ landslide area in south-west Slovakia , 2012, Natural Hazards.

[30]  D. Turcotte,et al.  Landslides and Earthquakes , 2002 .

[31]  M. Sorriso-Valvo,et al.  Logistic Regression analysis in the evaluation of mass movements susceptibility : The Aspromonte case study, Calabria, Italy , 2007 .

[32]  D. Varnes Landslide hazard zonation: A review of principles and practice , 1984 .

[33]  R. Soeters,et al.  Landslide hazard and risk zonation—why is it still so difficult? , 2006 .

[34]  I. Yilmaz Comparison of landslide susceptibility mapping methodologies for Koyulhisar, Turkey: conditional probability, logistic regression, artificial neural networks, and support vector machine , 2010 .

[35]  L. Ayalew,et al.  Landslides in Sado Island of Japan: Part II. GIS-based susceptibility mapping with comparisons of results from two methods and verifications , 2005 .

[36]  E. E. Brabb,et al.  Landslide susceptibility in San Mateo County, California , 1972 .

[37]  T. Kavzoglu,et al.  Assessment of shallow landslide susceptibility using artificial neural networks in Jabonosa River Basin, Venezuela , 2005 .

[38]  Manfred F. Buchroithner,et al.  Landslide Susceptibility Mapping by Neuro-Fuzzy Approach in a Landslide-Prone Area (Cameron Highlands, Malaysia) , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[39]  D. H. Lee,et al.  Mapping Slope Failure Potential Using Fuzzy Sets , 1992 .

[40]  D. Keefer The importance of earthquake-induced landslides to long-term slope erosion and slope-failure hazards in seismically active regions , 1994 .

[41]  P. Reichenbach,et al.  GIS techniques and statistical models in evaluating landslide hazard , 1991 .

[42]  John C. Davis,et al.  Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA , 2003 .

[43]  S. Sarkar,et al.  STATISTICAL MODELS FOR SLOPE INSTABILITY CLASSIFICATION , 1993 .

[44]  R. D. Garg,et al.  Evaluation of vertical accuracy of open source Digital Elevation Model (DEM) , 2013, Int. J. Appl. Earth Obs. Geoinformation.

[45]  Lucia Luzi,et al.  Influence of earthquakes on the stability of slopes , 2007 .

[46]  Jerome V. DeGraff,et al.  Regional Landslide—Susceptibility Assessment for Wildland Management: A Matrix Approach , 2020, Thresholds in Geomorphology.

[47]  Biswajeet Pradhan,et al.  Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area , 2011, Comput. Geosci..

[48]  M. Matteucci,et al.  Artificial neural networks and cluster analysis in landslide susceptibility zonation , 2008 .

[49]  Donald Robert Coates,et al.  Thresholds in Geomorphology , 2020 .

[50]  M. Eeckhaut,et al.  Prediction of landslide susceptibility using rare events logistic regression: A case-study in the Flemish Ardennes (Belgium) , 2006 .

[51]  Landslide Hazards in the Polish Flysch Carpathians: Example of Łososina Dolna Commune , 2013 .

[52]  A. Shakoor,et al.  A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses , 2010 .

[53]  T. Fernández,et al.  Methodology for Landslide Susceptibility Mapping by Means of a GIS. Application to the Contraviesa Area (Granada, Spain) , 2003 .

[54]  C. F. Lee,et al.  Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong , 2001 .

[55]  Saro Lee,et al.  Landslide susceptibility analysis using GIS and artificial neural network , 2003 .

[56]  Edgar Berrezueta,et al.  Landslides in the Central Coalfield (Cantabrian Mountains, NW Spain): Geomorphological features, conditioning factors and methodological implications in susceptibility assessment , 2007 .

[57]  A. Clerici A GRASS GIS based Shell script for Landslide Susceptibility zonation by the Conditional Analysis method , 2002 .

[58]  C. F. Lee,et al.  A spatiotemporal probabilistic modelling of storm‐induced shallow landsliding using aerial photographs and logistic regression , 2003 .

[59]  Saro Lee,et al.  Statistical analysis of landslide susceptibility at Yongin, Korea , 2001 .

[60]  B. Pradhan Manifestation of an advanced fuzzy logic model coupled with Geo-information techniques to landslide susceptibility mapping and their comparison with logistic regression modelling , 2011, Environmental and Ecological Statistics.

[61]  David G. Toll,et al.  CONTROLLING PARAMETERS FOR RAINFALL-INDUCED LANDSLIDES , 2002 .

[62]  Manoj K. Arora,et al.  A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas , 2006 .

[63]  Keith Smith Environmental Hazards: Assessing Risk and Reducing Disaster , 1991 .

[64]  C. Gokceoğlu,et al.  Landslide susceptibility mapping of the slopes in the residual soils of the Mengen region (Turkey) by deterministic stability analyses and image processing techniques , 1996 .

[65]  M. Marschalko,et al.  Landslide susceptibility assessment of the Kraľovany–Liptovský Mikuláš railway case study , 2010 .

[66]  Saro Lee,et al.  Determination and application of the weights for landslide susceptibility mapping using an artificial neural network , 2004 .

[67]  J. Blahůt,et al.  Spatial agreement of predicted patterns in landslide susceptibility maps , 2011 .

[68]  Işık Yilmaz,et al.  Structural and geomorphological aspects of the Kat landslides (Tokat—Turkey) and susceptibility mapping by means of GIS , 2006 .

[69]  M. Terlien,et al.  Prediction of the occurrence of slope instability phenomenal through GIS-based hazard zonation , 1997 .

[70]  F. Saboya,et al.  Assessment of failure susceptibility of soil slopes using fuzzy logic , 2006 .

[71]  Miloš Marjanovi LANDSLIDE SUSCEPTIBILITY MODELLING : A CASE STUDY ON FRUŠKA GORA MOUNTAIN , 2009 .

[72]  Saro Lee,et al.  Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data , 2005 .

[73]  Isik Yilmaz,et al.  Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat - Turkey) , 2009, Comput. Geosci..

[74]  Saro Lee,et al.  Use of an artificial neural network for analysis of the susceptibility to landslides at Boun, Korea , 2003 .

[75]  M. Ercanoglu,et al.  Adaptation and comparison of expert opinion to analytical hierarchy process for landslide susceptibility mapping , 2008 .

[76]  J. L. Parra,et al.  Very high resolution interpolated climate surfaces for global land areas , 2005 .

[77]  M. Bednarik,et al.  Different ways of landslide geometry interpretation in a process of statistical landslide susceptibility and hazard assessment: Horná Súča (western Slovakia) case study , 2010 .

[78]  Yong Liu,et al.  Neural network modeling for regional hazard assessment of debris flow in Lake Qionghai Watershed, China , 2006 .

[79]  M. Bednarik,et al.  Landslide susceptibility assessment using the bivariate statistical analysis and the index of entropy in the Sibiciu Basin (Romania) , 2011 .

[80]  S. Reis,et al.  A GIS-based comparative study of frequency ratio, analytical hierarchy process, bivariate statistics , 2011 .

[81]  Işık Yilmaz,et al.  The effect of the sampling strategies on the landslide susceptibility mapping by conditional probability and artificial neural networks , 2010 .

[82]  K. T. Chau,et al.  Regional bias of landslide data in generating susceptibility maps using logistic regression: Case of Hong Kong Island , 2005 .

[83]  Robert F. Legget,et al.  Engineering geological maps: a guide to their preparation: Book Review , 1978 .

[84]  B. Neuhäuser,et al.  GIS-based assessment of landslide susceptibility on the base of the Weights-of-Evidence model , 2012, Landslides.

[85]  William C. Haneberg,et al.  Rapid water-level fluctuations in a thin colluvium landslide west of Cincinnati, Ohio , 1994 .