Assessing Fire Risk Zones in Phrae Province, Northern Thailand, Using a MaxEnt Model

This study aimed to investigate the physical factors influencing the occurrence of forest fires and to create a fire risk map of Phrae Province. Remote sensing and geographic information system (GIS) technology were applied for the analysis, focusing on seven factors: the digital elevation model (DEM); slope; Normalized Difference Vegetation Index (NDVI); aspect; and distances from people, water, and roads. All of these geographical factors can affect forest fires. This resulted in a MaxEnt (Maximum Entropy) model with an AUC (area under the curve) of 0.849, indicating its great prediction ability. The findings revealed that the variables influencing forest fire incidence were the DEM, NDVI, slope, distance from roads, distance from water, distance from communities, and aspect, in that order. Subsequently, a fire risk map for wildfires was developed by reclassifying the data into five levels—very low risk, low risk, medium risk, high risk, and very high risk—accounting for 341,395.54, 88,132.64, 76,162.41, 81,157.55, and 57,384.10 hectares or 52.99, 13.68, 11.82, 12.60, and 8.91% of the total area, respectively. The areas classified as very high risk, high risk, medium risk, and low risk included the Song, Long, and Rong Kwang Districts. The area with the lowest risk was Nong Muang Khai District.