Landslides are significant natural hazards that alter the environment and negatively impact human lives and economies globally. Studying these phenomena is crucial in hilly regions, including the high hillsides of the Reshi River Basin, which are particularly susceptible to landslides due to climatic, geological, and geomorphological conditions. Initially, landslides in the Reshi River Basin were identified using Google Earth imagery. Thus, it is essential to create landslide susceptibility maps for the area. This study details the process of modelling landslide susceptibility using remote sensing data and GIS tools. Fourteen factors contributing to landslides—such as elevation, slope, curvature, lineament density, rainfall, drainage density, soil, lithology, relative relief, road density, settlement density, land use/land cover, and the topographic wetness index (TWI)—were analyzed. These factors were extracted from a spatial database created with remotely sensed data and topographic maps. The analysis involved weighting raster thematic maps, multiplying them by their respective weights, and combining them to generate a landslide susceptibility index (LSI) value for each cell. The final susceptibility map, after reclassification, includes four categories: low, moderate, high, and very high. According to the Linear Compositing Model (LCM), 90% of the identified landslide zones fall into the high and very high susceptibility categories. Vegetation plays a crucial role in preventing landslides by stabilizing the soil and reinforcing slopes. The roots of plants intertwine soil particles, which enhances the soil’s cohesion and tensile strength. This diminishes the likelihood of the soil breaking away and sliding down, particularly in the event of heavy rain or earthquakes. For this, the study also observed changes in vegetation cover between 2001 and 2016.