LANDSLIDE SUSCEPTIBILITY MAPPING IN THE SULTAN MOUNTAINS (AKŞEHIR, TURKEY) USING A BINARY LOGISTIC REGRESSION METHOD AND GIS

Globally, landslides cause hundreds of billions of dollars in damage and hundreds of thousands of deaths and injuries each year. Therefore, to mitigate any damage arising from landslides, it is necessary to scientifically assesses susceptible areas. The purpose of this study is to produce a landslide susceptibility map of the Sultan Mountains in central Turkey, based on a logistic regression method within a GIS environment. The field survey for this investigation mapped the location of landslides, and 90 landslides were determined in the study area. In this study, 19 landslide-affecting factors: geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total, plan, and profile curvatures, wetness index, stream power index, sediment transport capacity index, attitude, distance to drainage, distance to fault, drainage density, fault density, and spring density map, were used in the analysis. The coefficients of the predictor variables were estimated using binary logistic regression analysis and were used to calculate the landslide susceptibility for the entire study area. The accuracy of the final landslide susceptibility map was evaluated based on the observed landslides and by calculating relative operating characteristics curve. By overlaying the predicted landslide susceptibility map with the observed landslides data, the results indicated that 71 of the 90 observed landslides were correctly predicted. The area value of the relative operating characteristics curve model was found to be 0.940. These results indicate that the model is a good estimator of landslide susceptibility in the study area. The interpretations of the susceptibility map showed that geology, slope steepness, slope aspect, and elevation play a major role in landslide occurrence and distribution in the Sultan Mountains.