ORIGINAL RESEARCH article
Front. For. Glob. Change
Sec. Fire and Forests
Volume 8 - 2025 | doi: 10.3389/ffgc.2025.1635041
A Comparative Evaluation of Forest Fire Hazard Vulnerability Through Geographic Information System-Based Techniques
Provisionally accepted- 1Northeast Forestry University College of Forestry, Harbin, China
- 2Heilongjiang Agricultural Engineering Vocational College, Harbin, China
- 3University of Swat, Saidu Sharif, Pakistan
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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. 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). 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. 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.
Keywords: Fuzzy Logic, Dong model, Wildfire vulnerability, spatial risk analysis, Forest fire susceptibility
Received: 25 May 2025; Accepted: 29 Sep 2025.
Copyright: © 2025 Ahmad, Wu, Huang, Muhammad, Hayat, Abbas, Yang and Shu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Zhan Shu, shuzhan@nefu.edu.cn
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