Hasham Ahmad, Zhiyuan Wu, Hui Huang, Sultan Muhammad, Mansoor Hayat, K. Abbas, Xiguang Yang, Zhan Shu
Introduction Mapping forest fire risk is essential for effective prevention and efficient resource allocation, as it accurately assesses fire hazards across regions. This study conducts a comparative evaluation of the Analytical Hierarchy Process (AHP), the Fuzzy Analytical Hierarchy Process (F-AHP), and the Dong model for forest fire risk mapping in Liangshui National Nature Reserve by analyzing the weights of the factors contributing to fire risk. Methodology The forest fire risk maps were developed based on several contributing factors: aspect, elevation, slope, topographic wetness index, proximity to roads, distance to settlements, population density, Land Use Land Cover, temperature, precipitation, wind speed, normalized difference vegetation index (NDVI), and normalized difference moisture index (NDMI). Results Receiver Operating Characteristic (ROC) curve analysis was employed to validate and assess the predictive performance of the models. The evaluation of the Area Under the Curve (AUC) values revealed that the Analytical Hierarchy Process (AHP) model achieved high prediction accuracy with an AUC of 0.92, while the Dong model slightly lowered with an AUC of 0.91. In contrast, the Fuzzy Analytical Hierarchy Process (F-AHP) yielded an AUC of 0.90. These results indicate that the fire risk map generated by the AHP provides the most accurate and reliable prediction. Conclusion Overall, the findings underscore the effectiveness of the proposed modeling approaches and demonstrate their potential to enhance decision-making processes in forest fire risk management and the strategic allocation of prevention resources.