Wildfire Susceptibility Evaluation By Integrating An Analytical Network Process Approach Into Gis-Based Analyses
The northern area of Iran is exposed to wildfires, including forest fires and grassland fires. Since 2012, the area has experienced an increasing number of wildfires. They are a potential risk for the vulnerable communities residing close to the forestry areas. The main sources for the growing rate of wildfires are the increasing temperature and number of drought years in the last decade. However, besides the environmental and geographical reasons for wildfires, other factors also play a role, such as an increase in human activities during this period. In this study, our objective was to improve wildfire prediction and to reduce its effects by facilitating the development of wildfire mitigation plans. Spatial multi-criteria decision-making (S-MCDM) methods are commonly used to solve spatial problems that involve diverse factors. We herein used the analytical network process (ANP), as a central component of the MCDA methodology, to analyze 12 relevant factors for wildfire susceptibility mapping. The wildfire factors included topographic, climatologic, vegetation coverage and anthropological indicators. The final resulting susceptibility map was validated against a wildfire inventory database, which was prepared from MODIS hotspot data and an extensive field survey. Results of the validation approach indicated an 84% accuracy of the wildfire susceptibility map as a result of using the ANP method and the relevant factors.
Keywords- Wildfire, MODIS hotspots, Spatial multi-criteria decision-making (S-MCDM), analytical network process (ANP).