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

Area of Science:

• Environmental Science
• Forestry
• Geographic Information Systems (GIS)

Background:

• Forest fires pose significant threats to human life, property, and ecosystems.
• High-quality forest fire risk maps are essential for prevention, resource allocation, and decision-making.

Purpose of the Study:

• To develop and validate a novel multi-criteria decision analysis (MCDA) method for small-scale forest fire risk mapping.
• To assess and map forest fire risk in Youxi County, Fujian Province.

Main Methods:

• Utilized a multi-criteria decision analysis (MCDA) approach integrating geographic information systems (GIS).
• Employed the analytic network process (ANP) for factor importance analysis and weight assignment.
• Applied fuzzy logic assessment for sub-standard weight evaluation and ArcGIS for map generation.
• Validated the generated risk map using satellite fire points.

Main Results:

• Identified key factors influencing forest fire occurrences in Youxi County.
• Generated a forest fire risk map indicating severe risk in central and northern regions.
• The fuzzy ANP model achieved a high accuracy of 85.8% in risk assessment.
• A considerable proportion of the county was classified as level 4 or higher fire risk.

Conclusions:

• The novel MCDA method effectively improves the accuracy of small-scale forest fire risk mapping.
• The findings provide a basis for early fire warning systems and strategic allocation of firefighting resources.
• The study highlights the severe fire risk in specific regions of Youxi County, necessitating targeted management strategies.