landslide risk zoning potential by analytical hierarchy process (ahp) and multivariate regression (mr) (case study: upstream of north karoon basin)

in western and southern watersheds of isfahan province, combinations of natural and human factors have caused numerous landslides related damages. one of the main strategies for restricting the damage caused by the landslide is to avoid these regions. for this purpose, it is necessary to prepare precise landslide hazard zonation map for such areas. for this purpose, by aerial photos, satellite images, geological maps and field studies , landslide inventory map was prepared in of the upstream watersheds of karoon basin called marber river basin with an area of 800 square kilometers. then, nine factors including lithology, slope, land use, rainfall, vegetation cover, aspect, and lineaments elements such as road, fault and drainages were studied as 54 parameters. to enhance accuracy, speed and ease of analysis, all spatial and descriptive data were interred into gis and 27466 homogeneous units were obtained by overlapping of the mentioned map layers. analytical hierarchy process (ahp) and multivariate regression (mr) were used for multi criteria decision analysis and the results showed that both methods have the same accuracy in the separation of zones (lines) with the specific index of landslide risk.. but ahp approach of regression data, based on total quality index as an indicator of the accuracy of the learning has higher acceptability. this is related to this fact that the method has considered all 54 effective parameters due to the inherent performance of natural phenomena and events involved with the landslide. based on multivariate regression method, only 30 of 54 variables were significant at 95% and 99% levels and r coefficient of regression equation was 57% which is quite acceptable