Risk zone mapping of forest fire using Logistic Regression in GIS (Case study: Forest of ILAM County)

In recent years one of the major challenges is forest fire and loss of forest¡ and thus a fire hazard mapping and identification of fire-prone areas to manage these areas is very important for the executive departments. In this study¡ we have tried to map the risk of fire in the Zagros forests located in Ilam city (Given the importance of the various functions of this forests in terms of economic¡ social and environmental). This study was done using logistic regression modeling and geographic information system technology. The results of this study showed that the incidence of forest fires in the region associated with seven variable distance from population centers¡ population density¡ distance to roads¡ slope¡ oak¡ average maximum temperatures. According to the output equation of the logistic regression and probability and risk of wildfires in area¡ in total¡ the area is relatively large potential for the occurrence of forest fire. So that based on a map prepared in this study¡ about 45 percent of area was located in moderate classes to high risk classes and fire hazard threatened forests¡ grasslands¡ wildlife¡ welfare and recreation of people that have high dependence on these forests.