Fuzzy Logic Based Real-Time Prediction Model for Wild-Land Forest Fires

Wildland fires have consumed acres of land and affected natural habitat in ways beyond a common man’s intuition. More often than not, rescue operations including evacuation of surrounding urban areas have failed in saving the damage to life and property. Case studies of historical fires hold lack of situational awareness the biggest obstacle in forest fire-fighting. Eliminating the considerable rack of accurate information about fire-spread behavior can help fire-managers enhance safety of fire-personnel during on-field attacks. Fire-behavior study tools like FARSITE provide a good platform for study of historical fire and help in better understanding. Similar mathematical algorithms can be applied to real time environmental and spatial information to predict the spread of fireperimeters and intensities. Systems like this can be used with surveillance-based unmanned aircrafts and enable firefighters plan on-field fire-attacks and air-drops. The following is a step towards building such a system. The work uses topographical data from the GAP project for the West Virginia Land Cover. A decision making tool is developed using fuzzy logic to designate a fuel model for forestfires. This fuel model is then subjected to surface fire-spread techniques provided by Huygen’s Principle and Rothermel’s equation to develop a real time fire-predicting system.