AHP and fuzzy logic geospatial approach for forest fire vulnerable zones

Shatnawi, N.

Abstract: Fires are devastating risky events in forests, having a negative effect on resources, biodiversity, economics, animal life, and putting people in danger. The goal of this study is to use geospatial techniques to identify areas in Jordan that are at risk of forest fires. The research area extends 50 kilometers north and 15 kilometers east from the Dead Sea. The forest fire risk zones map was developed using six factors: land cover class, aspect, proximity to settlements, elevation, slope, and proximity to roads. All of the factors have been selected based on their fire sensitivity or capacity to cause fire. In this study, a Turkish model with fuzzy logic and Analytical hierarchy analysis (AHP) was utilized to classify the area into five categories of risk ranging from very low to very high. According to the findings, approximately 12.12% of the study area is classified as very low risk, 25.54 % is classified as medium risk, while 12.84% is classified as very high risk. Over the last ten years, the map has been confirmed by prior fire occurrences using data from civil defense archives. This conclusion was very useful in gaining an understanding of the geographical distribution of fire-vulnerable zones. The research found that the GIS approach combined with AHP and fuzzy logic is a useful tool for estimating such kinds of maps.

How to cite this paper

        APA: Shatnawi, N. (2022). AHP and fuzzy logic geospatial approach for forest fire vulnerable zones. Decision Science Letters, 11(4), 399-406.
    

        Chicago/Turabian: Shatnawi, N. 2022. "AHP and fuzzy logic geospatial approach for forest fire vulnerable zones." Decision Science Letters 11, no. 4 (2022): 399-406.
    

        AMA: Shatnawi, N. AHP and fuzzy logic geospatial approach for forest fire vulnerable zones. Decision Science Letters. 2022;11(4):399-406.
    

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