Affiliation:
1. National Institute of Technology, Patna, India
Abstract
This chapter aims to develop landslide susceptibility maps for the Sikkim state in India by combining the analytical hierarchy process, geographic information systems, and remote sensing. The delineation of the landslide susceptibility maps has taken into consideration a variety of data such as density of lineament, slope, lithology, aspect, land cover and land use, road buffer, rainfall, and drainage density. Using both Landsat 8 and ground data in a GIS framework, spatial distribution of maps and map layers of required themes were produced. The appropriate weights based on the Saaty's scale were given to these thematic layers in accordance with their respective significance in the occurrence of landslides in the study area. According to the study area's demarcated landslide susceptibility map, the risk levels were very low (12.52%), low (21.12%), moderate (8.05%), high (31.13%), and very high (27.18%). The accuracy of the study region is computed using the AUC curve using the AHP model landslide map and inventory map, which shows good result with 70% accuracy.