Sensitivity mapping of landslide occurrence by entropy and fuzzy logic models case study: Kermanshah city

Estimation of the ground to determine the zoning of sensitive areas movements, especially landslides range of research related to natural geographers is especially geomorphologists.Identification of sensitive areas to landslide can prevent the damages and also provide the capability for slope stabilization projects. In this paper landslide risk zoning is done by entropy and fuzzy methods. According to studies nine factors have been determined as the most important factors in landslide risk which include: lithology, distance from stream, distance from fault, distance from road, slope, aspect, altitude, land use and rainfall. By overlaying data layers, the effects of these factors on landslides in study area was reviewed in GIS, then the effect of them was evaluated and finally zoning map of landslide risk was provided by using these 9 factors. Evaluating by experimental probability index shows that fuzzy model with index of 90% is more capable than entropy method with index of 50% in landslide risk assessment in Kermanshah Township.