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Landslides are among the most common and hazardous natural disasters in mountainous environments, posing a significant threat to environmental sustainability and urban and human development. The risk becomes more severe in areas where geological, climatic, and human factors intersect, as is the case in the mountainous western region of Syria, which experiences recurrent landslides resulting in substantial damage to infrastructure, property, and threats to local populations. This study aims to produce a Landslide Susceptibility Map for the Khawabi River Basin in western Syria using spatial analysis techniques and Geographic Information Systems (GIS). A total of 33 documented landslide events were collected and divided into two subsets: 70% for training to build the predictive model, and 30% for testing to validate the results. Ten conditioning factors that are believed to influence landslide occurrence were selected for spatial analysis: lithology, elevation, slope, aspect, curvature, distance to faults, distance to roads, distance to rivers, land use/land cover (LULC), and the Topographic Wetness Index (TWI). Spatial modeling and mapping were performed using advanced GIS tools, and the study area was classified into different susceptibility zones ranging from low to very high. The results revealed that areas with very high landslide susceptibility are primarily concentrated along the steep eastern mountain slopes, where a combination of geological, topographical, and anthropogenic factors converge. The validation process using the testing dataset showed a high predictive accuracy of 91.2%, confirming the reliability and robustness of the applied model. This study highlights the importance of using remote sensing and GIS technologies for mapping natural hazard risks, providing accurate spatial information that can support landslide risk management and sustainable urban planning in western Syria. The study recommends integrating the findings into land-use policies and increasing public awareness about the importance of disaster risk reduction related to landslides.
Hazem Ghassan Abdo (Sat,) studied this question.