Keywords
analytic hierarchy process
certainty factor
landslide susceptibility
area under the curve
How to Cite
Abstract
The state of Himachal Pradesh in India is one of the most important hotspots when it comes to landslides; and Kandaghat, a tehsil in the Solan district of Himachal Pradesh having religious and tourism importance, is substantially affected by frequent landslides causing road blocking. In the present study, the analytic hierarchy process (AHP) and certainty factor (CF) techniques, which form part of the geographic information system (GIS)-based landslide susceptibility models, were used to prepare a landslide susceptibility map for the Kandaghat region, for which, as a preliminary step, an inventory of 214 live landslides was prepared from the Bhukosh data directory. The landslide inventory was cross-verified on the Google Earth platform. About nine landslide causative factors (slope, curvature, aspect, soil, rainfall, land use–land cover, lithology, drainage density and lineament density) were considered for the study area, and against the backdrop of these, the corresponding thematic maps were prepared and used in turn for the preparation of the final landslide susceptibility map. Based on the two mentioned techniques, the thematic maps were assigned weights according to their prominence and dynamic processes in the study area. The model performance for each method was evaluated using the area under the curve (AUC), and the accuracies for the AHP and CF were ascertained as, respectively, 81% and 85.6%. The Himalayan terrains are significantly prone to landslides, and this study outlines the characteristics of one of the important Himalayan towns in terms of vulnerability for landslides, together with providing its classification in terms of slope deformation susceptibility; this procedure can help direct attention towards areas needing to be classified under high to very high landslide susceptibility zones.
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