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GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations
Authors:Ali Yalcin
Institution:Department of Geological Engineering, Aksaray University, 68100, Aksaray, Turkey
Abstract:The Ardesen area is prone to landslides because of the climate conditions, geologic, and geomorphologic characteristics of the region. As in previous years, in 2001 due to heavy rainfall there were many landslides resulting in damage and human casualties. There is still a great danger of further landslides in the region. Therefore, it is vitally important to prepare a landslide susceptibility map of the region. In this study, the analytical hierarchy process (AHP), the statistical index (Wi), and weighting factor (Wf) methods were used to produce and later compare three susceptibility maps. For this purpose, thematic layers including landslide inventory, lithology-weathering, slope, aspect, land cover, distance to stream, drainage density, and distance to road were used. In this study area, 98% of landslides occurred in highly or completely weathered units. Lithology-weathering, land cover, and slope data layers were found to be important factors in the study area. To confirm the practicality of the three susceptibility maps were compared with a landslide activity map containing 16 active landslide zones. The outcome was that the active landslide zones do not completely fit into the high and very high susceptibility classes. But 81.3% of these landslide zones fall into the high and very high susceptibility zones of the AHP method while this is 62.5% in the case of Wi method, and 68.8% with the Wf method. In spite of the results obtained in this study, the development of a susceptibility map is usually determined by the needs and available resources. The results showed that the AHP method gave a more realistic picture of the actual distribution of landslide susceptibility, than the Wi and Wf methods.
Keywords:Landslide  GIS  Analytical hierarchy process  Bivariate statistics  Weathering
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