Forest fire hazard modeling using hybrid AHP and fuzzy AHP methods using MODIS sensor

Forest fire is one of the major natural risks in the north of Iran. It is impossible to control nature, but is possible to map forest fire risk zone and thereby minimize the risk of fire. The aim of this study is modeling the potential of forest fire in the Golestan forests by using Remote Sensing, GIS and aerologic data. The variables in this study must be weighted according to their impact on the forest fire hazard. Therefore analytical hierarchy process (AHP), and fuzzy-AHP, used to rank and prioritize the causative factors of fire risk in the study area. Fires occurred at 2010 in this zone and using the MODIS fire product dataset shown that majority of burned area were in the recommended risky places of this model by overall accuracy about 64%. Finally the sensitivity analysis applied to model wherein shown the fuel has highest degree of sensitivity.