Spatial assessment of wildfire risk using remote sensing and environmental variables in Thung Salaeng Luang national park, Thailand

Information from the abstract

This study aims to analyze factors influencing wildfire occurrence and generate a wildfire risk map for Thung Salaeng Luang National Park. Hotspot data were acquired using the satellite sensor of Suomi NPP and the VIIRS system over the study period ranging from 2021 to 2025, having a total of 420 hotspot records. Maximum Entropy Modeling was conducted on the relationship between the presence of wildfire hotspot occurrences and five environmental geographic variables extracted from the remote sensing data such as Elevation Above Sea Level, Slope, Aspect, NDVI, and LST. It is observed that the statistical model performed well in terms of prediction of wildfire risk with an AUC value of 0.812. The most influential factors for wildfire occurrence and spatial distribution were NDVI, LST, Slope, Elevation Above Sea Level, and Aspect. Based on the analysis of the wildfire risk assessment model, the wildfire risk zones of Thung Salaeng Luang National Park were divided into five different levels: very high/extreme risk, high risk, moderate risk, low risk, and lowest risk, which belong to the very low-risk level and cover 724.77 km² (58.22%) of the total area. Following this, there are low-risk areas, which cover an area of 227.16 km² (18.25%), moderate-risk areas, which cover 177.12 km² (14.23%), high-risk areas, which cover 97.47 km² (7.83%), and very high-risk areas, which cover 18.45 km² (1.48%). The very high-risk zones are predominantly distributed in Wang Thong District and Noen Maprang District. These findings provide essential spatial information for wildfire risk management planning by ranking the relative importance of environmental and geographic factors, thereby enabling more efficient mitigation of wildfire occurrence and reducing potential damage and associated impacts within this study area.

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Related topics: Fire effects on ecosystems · Fire Detection and Safety Systems · Species Distribution and Climate Change