Evaluation of prediction capability of the Statistical and Logestic models for mapping landslide susceptibility (Case Study: Vanakbasin)

The aim of this study is to produce landslide susceptibility mapping by Statistical models based on geographic information system (GIS) in the Southwestern of Isfahan Province,Vanak basin. First, the landslide locations were identified in the study area from interpretation of aerial photographs and multiple field surveys. 140 cases (70 %) out of 200 detected landslides were randomly selected for modeling, and the remaining 60 (30 %) cases were used for the model validation. The landslideconditioning factors, including slope degree, slope aspect, altitude, lithology, rainfall, distance to faults, density of streams, distance to road and land use were extracted from the spatial database. Using these factors, landslide susceptibility and weights of each factor were analyzed by logistic regression, density area and Certainty Factor models. The results of the models assessment showed that area density method by applying quality sum index (QS) is the highest value (0.35), then certainty factor and Logestic Regression are values of 0.29 and 0.11 in the next category, respectively. The interpretation of the susceptibility map indicated that altitude, rainfall and slope aspect play major roles in landslide occurrence in the study area These landslide susceptibility maps can be used for planning of land use , future road construction and hazard mitigation purpose.