Assessment of landslide susceptibility for Meghalaya (India) using bivariate (frequency ratio and Shannon entropy) and multi-criteria decision analysis (AHP and fuzzy-AHP) models

The main goal of the present study is to generate GIS-based landslide susceptibility map (LSM) Meghalaya, India. For this purpose, two bivariate statistical (FR and SE) multi-criteria decision analysis (AHP Fuzzy-AHP) methods are utilised. area situated over Shillong Plateau in North Eastern Region India subjected numerous landslides due heavy rainfall seismic activities. To obtain LSMs, a inventory 1330 events 15 conditioning factors prepared. dataset randomly split into 70/30 ratio make training testing datasets for study. results show that southern escarpment, southeast region hillslopes along roadsides highly susceptible landslide. LSMs validated using under curve (AUC) values F1-scores, which AHP (AUCAHP = 0.913; F1-score 0.884) shows highest prediction accuracy Meghalaya. generated can help risk mitigation strategies sustainable infrastructure development.