A GIS-Based Multicriteria Approach to Identifying Suitable Forest Depot Sites: A Case Study from Northern Türkiye

Natural disasters, particularly floods and landslides, can cause severe losses; however, their impacts can be significantly mitigated through proactive planning. In August 2021, a devastating flood in northern Türkiye resulted in major damage, including the displacement of logs from the Ayancık Forest Management Directorate’s depot, which exacerbated the disaster’s effects. This study aims to identify the most suitable location for a new forest depot in Ayancık, considering disaster risk, logistical needs, and environmental factors. A hybrid geospatial approach was employed by integrating Logistic Regression (LR)-based landslide susceptibility modeling and the Analytic Hierarchy Process (AHP). Key conditioning factors such as altitude, slope, aspect, lithology, land cover, plan and profile curvature, topographic wetness index (TWI), distance to drainage networks, roads, and faults were used to produce the LSM. The AHP weights of the factors used in selecting a suitable depot location were determined based on expert opinions. The integration of physical, logistical, and risk-based parameters allowed for a spatial prioritization of suitable areas. Results indicate that approximately 10.69% of the study area is classified as class 1 (very high suitability), 16.59% as class 2 (high), 20.71% as class 3 (moderate), 23.34% as class 4 (low), and 28.67% as class 5 (very low), corresponding to 27.28% of the area in classes 1–2 and 52.01% in classes 4–5. These results indicate that the study area is predominantly characterized by medium-low suitability conditions. Notably, these areas show significantly lower flood and landslide susceptibility compared to the current depot sites. By aligning forest infrastructure planning with disaster resilience principles, this study offers a replicable model for sustainable forest depot site selection. The findings provide valuable guidance for forest managers and policymakers to enhance the safety, functionality, and long-term viability of forestry operations in hazard-prone regions.