Abstract
The present study reflects the contributions of geo-environmental factors that were analyzed for the development of landslide hazard zonation map using certainty factor method and index of entropy method. Heavy rainfall, unscientific excavation of slopes during road construction, expansion of infrastructure, and unplanned growth in urban population were the major factors for unstable slopes in the Lesser Himalayan region. Historical database, interpretation of satellite and Google earth images were used to identification of 248 landslides. The data collected using remote sensing images have been verified by conducting ground truth surveys undertaken from January 2018 to October 2020 in preparing the landslide inventory of the study area. Inventory thus generated was divided into 70% training and 30% validation datasets. Relationships between slope failure and its causative factors (relief, slope, aspect, curvature, lithology, soil, weathering, land use, lineament density, rainfall, and density of drainage networks) were analyzed by using certainty factor (CF) and index of entropy (IOE) methods. The analysis of all causative factors and assigning relative weightage values by using the index of entropy and certainty factor models leads to the generation of Landslide hazard zonation maps of the region. Finally, the landslide prediction accuracy of hazard zonation maps was calculated by drawing Successive Rate Curve (SRC) curves for both training and validation datasets. The outcomes of this study will be useful to government agencies, planners, decision-makers, researchers, and general land-use planners for sustainable development of the study area.
GIS Based Multi-Criteria Decision Making for Landslide Hazard Zonation
