Wildfire hazard mapping using an ensemble method of frequency ratio with Shannon’s entropy

Abstract

This study investigates the capability of frequency ratio and an ensemble method of frequency ratio with Shannon’s entropy to produce a reliable map of wildfire susceptibility for Chaharmahal and Bakhtiari province, Iran. At first, the fire locations were identified in the study area from historical archives and field surveys. Ninety two cases (70%) out of 132 detected fire locations were randomly selected for modeling, and the remaining 40 (30 %) cases were used for the validation. Thirteen fire conditioning factors representing topography, climate, and human activities of the study area were extracted from the spatial database. Using the frequency ratio and the ensemble model, the relationship between the conditioning factors and fire locations were explored. The results were then used to produce distribution maps of wildfire hazard. The verification analysis using Receiver Operating Characteristic (ROC) curves and the Areas Under the Curve (AUC) revealed that the ensemble model with the capability of computing the weights of factors and their categories is more efficient than frequency ratio. The success and prediction rates for the frequency ratio and ensemble model were found to be 79.2 and 75.72%, and 85.16 and 82.92%, respectively. Further, the results suggest that more than one-third of the study area falls into the high and very high hazard classes, and the conditioning factors of land use, soil types, and distance from roads play major roles in fire occurrence and distribution in the study area