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Abstract

Forest fires represent a growing ecological and socio-economic concern, particularly in climate-sensitive and topographically complex landscapes. This study evaluates forest fire susceptibility across the Malakand Division of Khyber Pakhtunkhwa, Pakistan, using an integrated Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) framework. Nine parameters, including Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), precipitation, wind speed, slope, aspect, elevation, land use/land cover (LULC), and proximity to settlements, were derived from multi-source remote sensing data. These were assigned relative weights through AHP and synthesized via Weighted Overlay Analysis to construct a Forest Fire Risk Index (FFRI). The resulting susceptibility map categorized the region into five risk classes. Results showed that 33.22% of the area was classified as high risk and 19.01% as very high risk, correlating strongly with MODIS fire incident records from 2010 to 2025. Vegetation condition, temperature, and human proximity were identified as the most influential factors. These findings provide a robust geospatial decision-support tool for fire prevention, land-use planning, and sustainable resource management in a wildfire-prone environment. Keywords: Forest fire, Fire risk assessment, AHP, GIS, Remote sensing

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