The assessment of risk and damage landslide in the Baghi Basin with used Certainty Factor and logistic regression methods

Landslides are major natural hazards for human activities that often lead to loss of economic resources, damage to property and infrastructure, loss of life and destruction of natural landscapes. Landslide Susceptibility Mapping is a major step in risk management. Various models have been proposed for landslide hazard zonation that In this study, the efficiency of two models, multivariate regression analysis (logistic regression) and probabilistic model Certainty Factorin Nishapur Baghi basin was compared to the mapping of landslide risks, the best model for zoning be selected. 44 landslides Identify to in the region of case study and after correction and final approval, the landslide distribution map was prepared in GIS environment and were digitized. Then, based on 10 criteria contributing to landslides, including elevation, slope, aspect, lithology, faults, Pvshshgyahy index, land use, precipitation, distance from the road and away from river and with the map of each factor and integrate them with maps of potential landslides and using software and SPSS 10.2 ARC GIS and the methods, landslide hazard zoning map was prepared in 5 categories. The evaluate and select appropriate models for landslide hazard zonation was used landslide index (Li). Based on this index, the Certainty Factorof 92.32% and logistic regression 60.35 percent landslide occurred in the class’s high risk and very high risk. Certainty Factormethod was identified suitable for the study area. The results show that slope, lithology and height are the most important factors in the occurrence of landslides in the study area. The results of this study can be useful in the management of the risk of landslides and aggravating factors.