COMPREHENSIVE STUDY OF LANDSLIDE SUSCEPTIBILITY MAPPING FOR JAMMU & KASHMIR, INDIA USING GIS BASED BI-VARIATE PROBABILISTIC APPROACHES

Abstract

The Himalayan region of India is susceptible to landslides and its mitigation has always been of concern. Planners and local communities benefit from the study of landslide disasters for the development of an area that increases societal safety. The geological and topographical features of Jammu & Kashmir make it prone to natural hazards like landslides. Landslide Susceptibility mapping (LSM) of an area has proven to be efficient to detect hazardous zones. This research develops a zonation map for the Jammu & Kashmir, India using ArcGIS software to examine landslides as a risk. Twelve causal factors were found in the prepared land slide inventory to create the thematic maps. Major factors considered were elevation, stream power index (SPI), slope, aspect, topographic wetness index (TWI), curvature, average annual rainfall, lineament percentage, earthquake, land use land cover (LULC), distance from roads and lithology. Application of four bi-variate statistical models, namely Shannon Entropy, Frequency Ratio, Statistical Information Value and Weight of Evidence, have resulted in accuracy of 87.5%, 87.2%, 88.2% and 88.1% respectively, thus validating the maps devised. A thorough examination of LSM can help identify the area’s landslide-prone areas and their primary causes in advance, hence minimizing their adverse effects.