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Modeling forest fire risk based on GIS-based analytical hierarchy process and statistical analysis in Mediterranean region

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Abstract

This study proposed an integrated approach to generating a forest fire risk map. It used geographic information system–based multiple criteria decision analysis (GIS-MCDA) with the analytic hierarchy process (AHP) and a statistical index (SI). The research was carried out at the Mersin Regional Directorate of Forestry (RDF) in the eastern Mediterranean region of Turkey. Four main criteria, the forest structure, topography, environment, and climate, and 16 subcriteria were used to create the fire risk map. The weight of each criterion was determined using the AHP. The AHP model revealed that environmental factors are the most influential in igniting forest fires, followed by the forest structure. In order to evaluate the results, 990 historical forest fire ignition points were obtained from the Mersin RDF. According to the forest fire risk map, more than 85% of the ignition points were in areas classified as having an extreme or high risk for forest fires. The findings show that the study area is highly prone to forest fires. The relative operating characteristic curve and area under the curve were used to validate the accuracy of the fire risk map. This validation revealed a very high accuracy of 0.775 for the AHP model, indicating a high accuracy in forest fire risk mapping, and the map produced was consistent and reliable. The AHP model and its results will assist decision makers in taking necessary precautions to prevent forest fires and to minimize fire damage, particularly in the eastern Mediterranean region.

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2022-05-01

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Inverse distance weighted | MCDA | Pinus brutia | ROC | Topography | Turkey

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