Landslide Susceptibility Analysis of Shiv-Khola Watershed, Darjiling: A Remote Sensing & GIS Based Analytical Hierarchy Process (AHP)

In the present study, Remote Sensing Technique and GIS tools were used to prepare landslide susceptibility map of Shiv-khola watershed, one of the landslide prone part of Darjiling Himalaya, based on 9 landslide inducing parameters like lithology, slope gradient, slope aspect, slope curvature, drainage density, upslope contributing area, land use and land cover, road contributing area and settlement density applying Analytical Hierarchy Approach (AHA). In this approach, quantification of the factors was executed on priority basis by pair-wise comparison of the factors. Couple comparing matrix of the factors were being made with reasonable consistency for understanding relative dominance of the factors as well as for assigning weighted mean/prioritized factor rating value for each landslide triggering factors through arithmetic mean method using MATLAB Software. The factor maps/thematic data layers were generated with the help of SOI Topo-sheet, LIIS-III Satellite Image (IRS P6/Sensor-LISS-III, Path-107, Row-052, date-18/03/2010) by using Erdas Imagine 8.5, PCI Geomatica, Arc View and ARC GIS Software. Landslide frequency (%) for each class of all the thematic data layers was calculated to assign the class weight value/rank value. Then, weighted linear combination (WLC) model was implied to determine the landslide susceptibility coefficient value (LSCV or 'M') integrating factors weight and assigned class weight on GIS platform. Greater the value of M, higher is the propensity of landslide susceptibility over the space. Then Shivkhola watershed was classified into seven landslide susceptibility zones and the result was verified by ground truth assessment of existing landslide location where the classification accuracy was 92.86 and overall Kappa statistics was 0.8919.