Landslide risk modeling using fuzzy hierarchical analysis: thecase study of Savadkuh city

Landslides are one of the natural phenomena that cause a lot of financial and human losses in the country every year. Therefore, identifying landslide-prone areas to use methods to prevent or deal with slope instability is very important to reduce their hazard and risk. Landslides have always been a serious threat to human habitation. The aim of this study is to use the fuzzy hierarchical process method for landslide risk zoning in Savadkuh through information layers and factors affecting landslides. In the present study, using the landslide points taken from the city, landslide zones were identified in the region. Factors such as altitude, slope, aspect, geology, soil layer, land-use, distance from the fault, and distance from the road and the river were studied as influential variables in landslides. In order to prepare the layers and classify each of them for each variable, the method of combining the landslide layer and the desired variable was used, and in fact, the same method was used to determine the fuzzy membership using the frequency ratio model. After calculating the frequency ratio and fuzzy membership of the classes, the fuzzy set operators, including addition, multiplication, and gamma of 0.7, 0.8 and 0.9, were used as methods to overlap the classified variables with the fuzzy membership values to Landslide zoning maps should be prepared in the study area. In order to select the optimal method from fuzzy overlap operators, two methods of quality summation (Qs) and precision method (P) were used to determine which operator or fuzzy method has better accuracy for landslide risk zoning in Savadkuh. The value of the quality summation index, which shows the comparison and evaluation of methods in comparison with each other, indicates that the 0.8 gamma fuzzy operator has the highest value of Qs among other fuzzy operators