Forest Wildfire Potential Zoning Using Multi-criteria Decision Making Methods

Forests are one of the main natural resources on which human life depend. Nowadays, forests are going through the process of deforestation and many parts of them are destroyed for various reasons such as the global warming effect, carelessness of tourists, and "Slash and Burn". Increasing the water permeability rate and soil retention capacity, preventing soil erosion, reducing air pollution and being home to different plants and animals species, are examples of the main benefits of forests. Obviously, lack of forests results in several problems for human life. In order to preserve this main and valuable resource, one should first prevent the forest wildfire as much as possible, and second, if it is on fire one must stop its expansion and spread. Prevention of fire and controlling it when it happens, require recognition of the areas with thehigh potential for fire and taking necessary preventive measures for its spread. There are different studies on how to prepare risk zone maps. The final maps have been compiled through aweighted linear combination of the factors involved and good results have been achieved. In this research, high-risk zones are predicted using multi-criteria decision making along with spatial analysis. Analytic Hierarchy Process method (AHP) is a most widely weighting method and widely used because this is simple and break down thecomplexissue for simple and calculate weights using thepairwise comparison of criteria. In this paper, Analytic Hierarchy Process method (AHP) used to weighting criteria and two methods of fuzzy and OWA with linguistic quantifiers was used for overlay layers and result of those compare with quality sum method. The best QS is obtained through AHP_OWA for α4 where many percentages of fires occurred in the high or very high-risk zones, QS of this method shows ahigher value than gamma fuzzy method that shows better separation between risk zones and thus prepares risk zone maps with higher precision.