Forest Fire Risk Assessment Using Integrated Satellite Hotspot Data and Human Behavioral Factors: A Case Study of Lam Nam Nan National Park
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Abstract
This study aims to analyze the spatial relationships among historical hotspot data, human activities, and accessibility factors influencing forest fire occurrence, and to develop a spatial model for forest fire risk assessment in Lam Nam Nan National Park, Thailand. This study utilized five-year historical hotspot data from 2021 to 2025, forest product collection location data, used as a proxy for human behavior, and road network data. Spatial analysis techniques, including Kernel Density, Buffer Analysis, Reclassification, and Overlay Analysis, were applied using a Geographic Information System (GIS). The results indicate that high-risk areas are primarily located in regions with high hotspot density, intensive human activities, and easy accessibility, particularly in the eastern, northeastern, and southern parts of the study area. In contrast, areas located farther from access routes and with lower human activity exhibit lower fire risk levels. The developed model classifies forest fire risk into four levels: high, moderate, low, and very low, with most of the area categorized as low risk. The findings demonstrate that integrating hotspot data with human behavior and accessibility factors enhances the effectiveness of forest fire risk assessment and can support proactive fire management planning in protected areas.
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