Spatial implementation of frequency ratio, statistical index and index of entropy models for landslide susceptibility mapping in Al-Balouta river basin, Tartous Governorate, Syria

Abstract Landslide vulnerability prediction maps are among the most important tools for managing natural hazards associated with slope stability in river basins that affect ecosystems, properties, infrastructure and society. events hazardous patterns of instability coastal mountains Syria. Thus, main goals this research to evaluate performance three different statistical outputs: Frequency Ratio (FR), Statistical Index (SI) Entropy (IoE) therefore map landslide susceptibility region To end, we identified a total 446 locations events, based on preliminary inventory derived from fieldwork high-resolution imagery surveys. In regard, 13 geo-environmental factors have high influence landslides were selected mapping. The results indicated FR method outperformed SI IoE models AUC 0.824 better adaptability, followed by 0.791. According SCAI values, although model achieved best reliability, other two also showed good capability determining susceptibility. result FR-based modelling 18.51 19.98% study area fall under very susceptible categories, respectively. generated method, about 36% is classified as having or sensitivity. whereas 14.18 25.62% “very susceptible” “high susceptible,” relative importance analysis demonstrated aspects, lithology proximity roads effectively motivated acceleration material influential both models. On hand, faults roads, along factor, influences formation events. As result, bivariate models-based mapping provided reliable systematic approach guide long-term strategic planning procedures area.