Landslide susceptibility assessment using weighted linear combination and InSAR with emphasis on tectonic influences: Insights from Salas Babajani County, western Iran

Natural hazards cause significant damage each year in many regions. Among the natural hazards affecting numerous regions—including Salas Babajani County in western Iran—landslides pose a significant threat. Owing to its environmental and tectonic conditions, Salas Babajani County is particularly prone to slope failure. Therefore, this study aims to delineate landslide-susceptibility zones within the county. The analysis employed the Weighted Linear Combination (WLC) model, Relative Weighting Factor method, and SAR interferometry. First, overall landslide-prone areas were mapped; then, special attention was given to areas exhibiting vertical displacement resulting from the 2017 Ezgeleh earthquake. The susceptibility assessment indicates that 25% of Salas Babajani County, primarily its northern sector, falls into high and very high vulnerability classes, with 26 villages (14% of total settlements) located within these high-risk zones. Interferometric analysis of the 2017 seismic event shows vertical displacements between +358 mm and –613 mm across the study area, with the greatest movements in its northern parts. The integration of datasets revealed that northern Salas Babajani County—where high environmental susceptibility coincides with vertical displacement exceeding 400 mm—represents a critical compound hazard zone requiring urgent mitigation. The susceptibility model demonstrated strong predictive capability, with 92.3% of recorded landslides falling within high and very high susceptibility classes. Taken together, the results demonstrate that northern Salas Babajani County, characterized by both unfavorable environmental parameters and pronounced vertical displacement, is highly susceptible to landslides. This integrated approach provides a transferable methodological framework for landslide hazard assessment in other tectonically active mountainous regions worldwide.