Resilience Assessment of Forest Fires Based on a Game-Theoretic Combination Weighting Method
Year: 2025
Type: article
Abstract: The increasing frequency and severity of forest fires, driven by climate change and intensified human activities, pose substantial threats to ecological security and sustainable development. However, most assessments remain centered on occurrence risk, lack a resilience-oriented perspective and comprehensive indicator systems, and therefore offer limited guidance for building system resilience. This study developed a forest fire resilience (FFR) assessment framework with 25 indicators in three levels and six domains across four resilience dimensions. Balancing expert judgment and data, we obtained indicator weights by integrating the Analytic Hierarchy Process (AHP) and the Criteria Importance Through Intercriteria Correlation (CRITIC) via a game-theoretic scheme. The analysis revealed that, among the level-2 indicators, climate factors, infrastructure, and vegetation characteristics exert the greatest influence on FFR. At the level-3 indicator scale, monthly minimum relative humidity, fine fuel load per unit area, and the deployment of smart monitoring systems were critical. Among the four resilience dimensions, absorption capacity plays the predominant role in shaping disaster response. Building on these findings, the study proposes targeted strategies to enhance FFR and applies the assessment framework to twelve administrative divisions of Baise City, China, highlighting marked spatial variability in resilience levels. The results offer valuable theoretical insights and practical guidance for strengthening FFR.
Source: Sustainability
DOI: 10.3390/su17177907
Authors: Zhengtong Lv, Junqiao Xiong, Mingfu Zhuo, Yuxian Ke, Qian Kang
Institution: Jiangxi University of Science and Technology
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
SDGs: Life on land, Climate action
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W4413927753
