Mapping Ecological Sensitivity for Restoration-Oriented Planning in Mediterranean Mountain Landscapes

Effective environmental monitoring and sustainable landscape management require spatially explicit approaches that can identify ecologically sensitive areas and support targeted conservation and restoration planning. Although Geographic Information Systems (GIS) and multi-criteria decision-making approaches are widely used for ecological sensitivity assessment, integrated frameworks that simultaneously account for biophysical conditions and anthropogenic pressures remain limited in data-scarce Mediterranean mountain environments. This study develops a GIS–AHP framework to assess ecological sensitivity in the Safita region of western Syria by integrating eleven climatic, topographic, hydrological, biophysical, land-use, demographic, and infrastructure-related criteria. The criteria were standardized, weighted using the Analytic Hierarchy Process (AHP), and integrated through a weighted linear combination to derive a spatially explicit Ecological Sensitivity Index (ESI). Moderate and High sensitivity classes dominated the study area, accounting for 55.3% and 35.5%, respectively, whereas the Extremely High class occupied only 0.29%. Vegetation, Soil, Rainfall, and LULC were the dominant criteria, collectively representing 70.08% of the total AHP weight. Sensitivity analysis demonstrated 100% stability in the criterion ranking across all ±10% weight-perturbation scenarios, while 93.9–97.1% of valid raster cells retained their baseline ESI class in the spatial-output tests. Spatial analysis showed that Safita Center and the northern and northeastern sectors contain extensive areas of elevated sensitivity and therefore warrant particular attention for environmental monitoring and restoration-oriented planning. In this context, the high contribution of vegetation reflects the ecological value and disturbance sensitivity of densely vegetated areas rather than environmental degradation per se. The resulting ESI should therefore be interpreted as an integrated measure of relative ecological sensitivity arising from the interaction of intrinsic environmental susceptibility and anthropogenic pressure, rather than as a direct measure of environmental degradation. The proposed framework provides a transparent and reproducible decision-support approach for prioritizing monitoring, conservation, and restoration actions in data-scarce Mediterranean mountain landscapes.