Integrating GIS and AHP for Forest Fire Risk Mapping in Kailali, Nepal

Abstract

Forest are the Earth’s predominant geographical phenomena distributed throughout the world and provide essential ecosystem services and products that benefit both humans and wildlife. The sustainability of the forest resources can be seriously affected by the forest fire in the dry regions covered with fire sensitive trees species. The risk of the forest fire mainly depends on the various factors such as vegetation type, topographical features, climatic parameters, socio-economic factors. Geographic Information System (GIS) and Remote Sensing (RS) technologies are frequently used for the monitoring, detection, and management of forest fires. Seven parameters: land cover, elevation, slope, aspect, land surface temperature (LST), and proximity to settlement and road were compared with each other and pair wise matrix was formed. The weight of each parameters was determined by using AHP technique. Then by using the raster calculator weighted-overlay analysis was performed to determine the final forest fire risk zone. The forest fire risk zone was categorized into five classes; very high-risk zone, high risk zone, moderate risk zone, low risk zone, and very low risk zone. The result indicated that there is a very high risk of forest fire in about 30.78%, a high risk in 34.06%, a moderate risk in 22.45%, a low risk in 9.87% and very low risk in 2.84% of total area of Kailali district.