Landslide susceptibility mapping using MT-InSAR and AHP enabled GIS-based multi-criteria decision analysis

Landslide susceptibility maps (LSMs) are generally prepared by integrating multiple prominent thematic layers, including DEM derived products (elevation, slope, and aspect), other parameters such as lithology, geomorphology, LULC, etc. These can be assigned optimum weights using the analytic hierarchy process (AHP) method, followed a GIS-based weighted overlay analysis. In recent years, multi-temporal interferometric synthetic aperture radar (MT-InSAR) techniques have been rigorously explored, for land deformation detection monitoring, extracting highly stable measurement pixels tens of SAR acquisitions simultaneously. this research work, multi-criteria decision analysis to prepare LSMs is proposed, with MT-InSAR displacement estimates used critical input parameter. An LSM generated processing 20 ERS-1/2 Envisat ASAR images, acquired over ?120 sq. km wide river basin, located in Uttarakhand, India. The found congruent susceptible made available Geological Survey India (GSI) under National Susceptibility Mapping (NLSM) program. Preliminary results indicate that majority unstable zones along Alaknanda River correctly identified. approach further implemented generate an updated map 60 scenes freely Sentinel-1A dataset, validation through actual field survey. This resulted generation map, which helped identification 44.5% new landslide (LSZs). Furthermore, status previously identified also quantified. performance proposed suggests its usability generating updating near-real-time LSMs.