Landslide Susceptibility Mapping Using Weighted Overlay Analysis

Abstract

In India's Upper Himalayas, in the state of Uttarakhand, the Bhilangana Basin is having fragile geologically and topographically complicated area where landslides occur very often. Based on the application of the Analytical Hierarchy Process (AHP) combined with the Weighted Overlay analysis method within a GIS environment, the study helps to make map landslide susceptibility zones in the bhilangna river basin. According to their geomorphological, climatic condition, and human intervention play a major role for landslide, in the study we using ten causative factors which were chosen for study such as slope, digital elevation model (DEM), rainfall, curvature, land use/land cover (LULC), normalized difference vegetation index (NDVI), aspect, relative relief, distance from roads, and distance from rivers. AHP-derived weights identified slope (20%), road distance (18%), rainfall (14%), and river distance (13%) as the most significant factors. The combined susceptibility map categorized the basin into Low (40.6%), Moderate (46.0%), and High (11.97%) risk zones. High-risk areas, though in a narrow range of coverage, are practically all clustered in mid-elevation belts with high slopes, barren land, concave topography, and proximity to road and river networks. These zones pose high risks to infrastructure, transport, and settlement, that need site-specific mitigation work such as stabilization of slopes, improved drainage, and re-establishment of vegetation. The approach demonstrates the value of multi-criteria decision analysis for landslide hazard evaluation in mountainous regions and can be applied to disaster preparedness and land-use management in other mountain regions. Patients. These predictors still require additional work to establish reliability. The thematic maps that were partitioned into risk values and susceptibility classes were prepared from satellite, field, and secondary data.