Evaluating of Quantitative Geomorphometric Parameters Efficiency in Increasing the Accuracy of Landslide Sensitivity Maps (Case Study: Fereydoun Shahr Basin, Isfahan Province)

One of the goals of geomorphologists in working with the models of different landforms is to obtain better relations in realizing the physical realities of environment. In this study, to evaluate the performance of geomorphometric parameters to increase accuracy of zoning landslide susceptibility map has been studied. As the first step by the application of nine initial conditioning factors including slope, aspect, elevation, land use, lithology, distance from roads, rivers and vegetation index (NDVI) the zoning map was provided. In the next step geomorphometric parameters influential on the occurrence of landslide including topographic location index (TPI), surface curvature, curved sections, slope length (LS), Topographic wetness index (TWI), stream flow power (SPI), surface area ration index (SAR), was added to the model and then the zoning map was obtained. In the final step, the zoning maps was evaluated by using ROC curve. To provide zoning maps a new mixed model was applied, so, for determination of criteria weights multivariate regression and to determine weight of the classes' frequency ratio method was utilized. The findings of this research indicated that geomorphometric factors have a considerable influence on the increase of identification of regions that are susceptible to the landslides and enhance the accuracy of zoning maps from 0.731 to 0.938. These factors have also increased the resolution of the slip classes. According to the results, topography position index, plan curvature and surface area ratio have the highest influence on the accuracy of zoning maps. Based on superior approach, 8.68% (6737 ha) of the region are at very high risk and 15.3% (11906 ha) have been identified as high risk areas. According to the high ability of geomorphologic parameters in the identification of susceptible areas to the landslide, the application of these parameters is recommended in landslide hazard zonation.