Landslide susceptibility mapping based on frequency ratio and logistic regression models

The aim of this study is to apply and compare a probability model, frequency ratio and statistical model, and a logistic regression to Sajaroud area, Northern Iran using geographic information system. Landslide locations of the study area were detected from interpretation of aerial photographs and field surveys. Landslide-related factors such as elevation, slope gradient, slope aspect, slope curvature, rainfall, distance to fault, distance to drainage, distance to road, land use, and geology were calculated from the topographic and geology map and LANDSAT ETM satellite imagery. The spatial relationships between the landslide location and each landslide-related factor were analyzed and then landslide susceptibility maps were produced using the frequency ratio and forward stepwise logistic regression methods. Finally, the maps were tested and compared using known landslide locations, and success rates were calculated. Predicted accuracy values for frequency ratio (79.48%) and logistic regression models showed that the map obtained from frequency ratio model is more accurate than the logistic regression (77.4%) model. The models used in this study have shown a great deal of importance for watershed management and land use planning.

[1]  Manfred F. Buchroithner,et al.  Utilization of optical remote sensing data and geographic information system tools for regional landslide hazard analysis by using binomial logistic regression model , 2008 .

[2]  V. Doyuran,et al.  Data driven bivariate landslide susceptibility assessment using geographical information systems: a method and application to Asarsuyu catchment, Turkey , 2004 .

[3]  A. Yalçın.  GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations , 2008 .

[4]  G. Bonham-Carter.  Geographic Information Systems for Geoscientists: Modelling with GIS , 1995 .

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

[6]  C. F. Lee,et al.  Landslide characteristics and, slope instability modeling using GIS, Lantau Island, Hong Kong , 2002 .

[7]  R. Soeters,et al.  LANDSLIDES: INVESTIGATION AND MITIGATION. CHAPTER 8 - SLOPE INSTABILITY RECOGNITION, ANALYSIS, AND ZONATION , 1996 .

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

[9]  F. Pergalani,et al.  Slope Instability Zonation: a Comparison Between Certainty Factor and Fuzzy Dempster–Shafer Approaches , 1998 .

[10]  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 .

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

[12]  B. Pradhan,et al.  Remote Sensing and GIS-based Landslide Susceptibility Analysis and its Cross-validation in Three Test Areas Using a Frequency Ratio Model , 2010 .

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

[14]  Matthew C. Larsen,et al.  How wide is a road? The association of roads and mass-wasting in a forested montane environment , 1997 .

[15]  H. A. Nefeslioglu,et al.  Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey , 2006 .

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

[17]  Chris S. Renschler,et al.  Geomorphology and ecosystems: Challenges and keys for success in bridging disciplines , 2007 .

[18]  K. T. Chau,et al.  Landslide hazard analysis for Hong Kong using landslide inventory and GIS , 2004, Comput. Geosci..

[19]  P. Reichenbach,et al.  Probabilistic landslide hazard assessment at the basin scale , 2005 .

[20]  P. Reichenbach,et al.  Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy , 1999 .

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

[22]  M. R. Peart,et al.  Landslides and sediment delivery to a drainage system: some observations from Hong Kong , 2005 .

[23]  Huang Jingfeng,et al.  GIS-based logistic regression method for landslide susceptibility mapping in regional scale * , 2006 .

[24]  Saro Lee,et al.  Probabilistic landslide susceptibility and factor effect analysis , 2005 .

[25]  Saro Lee,et al.  Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea , 2004 .

[26]  T. Korme,et al.  Natural hazard assessment using GIS and remote sensing methods, with particular reference to the landslides in the Wondogenet Area, Ethiopia , 2001 .

[27]  M. Arora,et al.  GIS-based Landslide Hazard Zonation in the Bhagirathi (Ganga) Valley, Himalayas , 2002 .

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

[29]  P. Frattini,et al.  Geomorphological and historical data in assessing landslide hazard , 2003 .

[30]  R. Anbalagan,et al.  Landslide hazard evaluation and zonation mapping in mountainous terrain , 1992 .

[31]  P. Reichenbach,et al.  Gis Technology in Mapping Landslide Hazard , 1995 .

[32]  José I. Barredo,et al.  Comparing heuristic landslide hazard assessment techniques using GIS in the Tirajana basin, Gran Canaria Island, Spain , 2000 .

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

[34]  B. Pradhan,et al.  Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models , 2010 .

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

[36]  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 .

[37]  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 .

[38]  Lucia Luzi,et al.  Slope vulnerability to earthquakes at subregional scale, using probabilistic techniques and geographic information systems , 2000 .

[39]  B. Pradhan,et al.  Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models , 2007 .

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

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

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

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

[44]  Hassan Ahmadi,et al.  Landslide susceptibility analysis with a bivariate approach and GIS in Northern Iran , 2009 .

[45]  E. Harp,et al.  A method for producing digital probabilistic seismic landslide hazard maps , 2000 .

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

[47]  E. Yesilnacar,et al.  Landslide susceptibility mapping : A comparison of logistic regression and neural networks methods in a medium scale study, Hendek Region (Turkey) , 2005 .

[48]  A. Clerici,et al.  A procedure for landslide susceptibility zonation by the conditional analysis method , 2002 .

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

[50]  Chang-Jo Chung,et al.  Two models for evaluating landslide hazards , 2006, Comput. Geosci..

[51]  C. Gokceoğlu,et al.  Use of fuzzy relations to produce landslide susceptibility map of a landslide prone area (West Black Sea Region, Turkey) , 2004 .

[52]  M. H. Tangestani.  A comparative study of Dempster–Shafer and fuzzy models for landslide susceptibility mapping using a GIS: An experience from Zagros Mountains, SW Iran , 2009 .

[53]  Y. Mitani,et al.  Spatial probabilistic modeling of slope failure using an integrated GIS Monte Carlo simulation approach , 2003 .

[54]  Zhaohua Chen,et al.  Landslide hazard mapping using logistic regression model in Mackenzie Valley, Canada , 2007 .

[55]  D. Hosmer,et al.  Applied Logistic Regression , 1991 .

[56]  C. F. Lee,et al.  Logistic regression modelling of storm-induced shallow landsliding in time and space on natural terrain of Lantau Island, Hong Kong , 2004 .

[57]  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..

[58]  H. A. Nefeslioglu,et al.  Susceptibility assessments of shallow earthflows triggered by heavy rainfall at three catchments by logistic regression analyses , 2005 .

[59]  B. Pradhan.  Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia , 2010 .

[60]  E. E. Brabb.  Innovative approaches to landslide hazard and risk mapping , 1985 .

[61]  S. Z. Mousavi,et al.  GIS-based spatial prediction of landslide susceptibility using logistic regression model , 2011 .

[62]  T. Topal,et al.  GIS-based landslide susceptibility mapping for a problematic segment of the natural gas pipeline, Hendek (Turkey) , 2003 .

[63]  B. Pradhan,et al.  Use of geospatial data and fuzzy algebraic operators to landslide-hazard mapping , 2009 .

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

[65]  Saro Lee,et al.  Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models , 2006 .