Forest fire risk zoning based on fuzzy logic and analytical network process

Ying Yong Sheng Tai Xue Bao. 2024 Feb;35(2):354-362. doi: 10.13287/j.1001-9332.202402.024.

Abstract

Forest fires have a significant impact on human life, property safety, and ecological environment. Deve-loping high-quality forest fire risk maps is beneficial for preventing forest fires, guiding resource allocation for firefighting, assisting in fire suppression efforts, and supporting decision-making. With a multi-criteria decision analysis (MCDA) method based on geographic information systems (GIS) and literature review, we assessed the main factors influencing the occurrences of forest fires in Youxi County, Fujian Province. We analyzed the importance of each fire risk factor using the analytic network process (ANP) and assigned weights, and evaluated the sub-standard weights using fuzzy logic assessment. Using ArcGIS aggregation functions, we generated a forest fire risk map and validated it with satellite fire points. The results showed that the areas classified as level 4 or higher fire risk accounted for a considerable proportion in Youxi County, and that the central and northern regions were at higher risk. The overall fire risk situation in the county was severe. The fuzzy ANP model demonstrated a high accuracy of 85.8%. The introduction of this novel MCDA method could effectively improve the accuracy of forest fire risk mapping at a small scale, providing a basis for early fire warning and the planning and allocation of firefighting resources.

林火对人类生命财产安全和生态环境产生重要影响,编制高质量的森林火险图对预防林火的发生、指导扑救资源配置、辅助火灾扑灭和支持决策制定均有积极意义。本研究采用基于地理信息系统的多准则决策分析(MCDA)方法以及查阅文献确定影响福建省尤溪县林火发生的主要因子,每个火险因子的重要性利用网络层次分析法(ANP)确定,得出权重,次标准的权重由模糊逻辑评估,使用ArcGIS的聚合函数生成森林火灾风险图,结合卫星火点验证准确度。结果表明: 尤溪县4级及以上火险等级区域占比大,中部和北部林火发生风险较高,该县整体火险情况严峻;模糊ANP模型的准确性较高,达85.8%。引入新的MCDA方法有效地提高了小尺度范围森林火险制图的准确度,可为早期林火预警、扑灭资源规划和分配工作提供依据。.

Keywords: GIS-based multi-criteria decision analysis (MCDA); analytical network process (ANP); forest fire risk mapping; fuzzy logic.

Publication types

  • Review

MeSH terms

  • Fires / prevention & control
  • Forests
  • Fuzzy Logic*
  • Geographic Information Systems
  • Humans
  • Trees
  • Wildfires* / statistics & numerical data