Abstract
The occurrence of landslides generally depends on complex interactions among a large number of partially interrelated factors. It is appropriate to use multivariate analysis for predicting landslides from a given set of independent variables. However, the procedure of landslide hazard assessment by regression analysis requires the evaluation of the spatially varying terrain conditions as well as spatial representation of the landslides. In this paper, multivariate regression analysis was applied to predict landslides in the Himi district from independent factors, such as geology, clinal-aspect, slope angle, land use and soil using Geographic Information System (GIS) . Based on GIS, every factor was classified into several categories and then the statistical weight of every cluster was assigned for every factor respectively. By the weights of five factors, the linear regression's coefficients of these input factors in landslide area were extracted and assigned to the whole region, and then the susceptibility for the potential landslide was obtained to make the landslide hazard assessment map. According to the coefficients in the Himi district, geology and clinal-aspect factors are the most important ones. Soil factor is not so notable in this research region, though it may be significant in other regions. Finally, the average susceptibilities map for existing landslides was made for the engineers to do control work.
