Landslide susceptibility mapping (LSM) of Swat District, Hindu Kush Himalayan region of Pakistan, using GIS-based bivariate modeling

Landslides are a recurrent environmental hazard in hilly regions and affect the socioeconomic development Pakistan. The current study area is tourism hydro energy hub of Pakistan affected by hazard. A landslide susceptibility mapping (LSM) Hindu Kush Himalayan, Swat District, Pakistan, can be created to reduce demographic losses due landslides. This conducted apply three bivariate models, including weights evidence (WOE), frequency ratio (FR), information value (IV) for an LSM that has not been explored or applied area. For this purpose, first, inventory map 495 landslides was constructed from both ground satellite data randomly divided into training (70%) testing (30%) datasets. Furthermore, 10 conditioning factors (elevation, slope, aspect, curvature, fault, rainfall, land use cover (LULC), lithology, road, drainage) used were prepared ArcGIS 10.8. Finally, generated based on WOE, FR, IV models validated performance using under receiver operating characteristic curve (AUROC). findings success rate (SRC) 67%, 93%, 64%, respectively, while prediction curves (PRCs) 87%, 95%, 73%, respectively. validation results justified FR model most reliable technique all these produce highest accuracy present Policymakers research work mitigate loss