1. Introduction
The escalation of military threats, such as air and drone attacks, along with advancements in technologies like F-35 fighters and precision-guided systems, has driven urban planning and crisis management toward advanced spatial analysis tools (Blaikie et al., 2013). Khorramabad, the capital of Lorestan Province in western Iran, is a strategic military target due to the presence of Imam Ali Barracks, making it vulnerable to potential attacks (Shakiba & Mousavi, 2019). The region’s topography, including slope, visibility, and proximity to strategic targets, significantly influences its vulnerability. This study aims to evaluate Khorramabad’s topographic and spatial vulnerability using Geographic Information Systems (GIS) and Digital Elevation Model (DEM) data to produce a comprehensive vulnerability map.
.2. Methods and Material
GIS-based methods were employed using 30-meter resolution DEM data from the Shuttle Radar Topography Mission (SRTM). Slope was calculated with the ArcGIS Pro Slope tool and categorized into 0–5°, 5–15°, and >15°. Viewshed analysis was conducted using Imam Ali Barracks as the observation point, while Euclidean Distance classified areas into 0–500 m, 500–1000 m, and 1000–10000 m from the barracks. Layers were integrated using Weighted Overlay, assigning 40% weight to distance, 30% to slope, and 30% to visibility, with validation using OSM data (30% weight). Geometric accuracy was ensured through field data comparison.
3. Results and Discussion
Results indicate that 6.56% of the city (4.79 km²) falls within the high vulnerability zone, primarily in western Khorramabad, characterized by slopes of 0–5°, distances less than 1000 m, and high visibility. Moderate vulnerability covers 72.43% (52.83 km²), while low vulnerability encompasses 21.01% (15.38 km²) of the city. The 40% weighting of distance highlights its critical role in vulnerability assessment, consistent with prior GIS-based studies (Kim et al., 2004).
4. Conclusion
This study confirms GIS as an effective tool for identifying high-risk areas and recommends reinforcing infrastructure, establishing urban shelters, and planning emergency evacuation routes in western Khorramabad. Future research could enhance model accuracy by incorporating population, land-use data, building density, and dynamic indicators such as climate variations.