GIS Based Forest Fire Susceptibility Modelling Using Frequency Ratio: A Case Study in Palpa District

Abstract

Forest fires in today’s world have become a serious problem affecting the environment, economy, humans, and the global ecosystem. The integration of GIS-based methods and remote sensing imagery is widely used to assess forest fire-prone areas. This study applied the Frequency Ratio (FR) method to evaluate spatial fire susceptibility by analyzing the relationship between historical fire hotspots and contributing factors in Palpa District, Nepal. A total of 330 fire hotspots from 2014 to 2024 were spatially digitized to create an inventory map of historical forest fire events. These hotspots were divided into two groups: 65% (217 points) for training and 35% (113 points) for validation. Forest fire causative factors were categorized into biological (land cover types, NDVI), meteorological (temperature, wind speed), topographic (slope, elevation, aspect), and human-driven (distance from roads, distance from settlements), and were used as parameters to assess the forest fire susceptibility map.The study area was classified into five fire susceptibility zones: very high, high, moderate, low, and very low. The results indicate that high- and moderate-risk zones cover the largest proportion of the area (350.23 km² and 386.21 km², respectively) and together account for more than 60% of recorded fire hotspots. Very high-risk areas, although spatially limited (201.90 km²), also show a significant concentration of past fire incidents. In contrast, low- and very low-risk zones exhibit comparatively fewer hotspots, confirming lower fire susceptibility. The strong correspondence between FR-derived risk classes and historical fire occurrences demonstrates the reliability of the FR method for fire susceptibility mapping. These findings provide valuable support for prioritizing fire prevention, monitoring, and resource allocation in Palpa District.