Gis and fuzzy logic approach for forest fire risk modeling in the Cajamarca region, Peru
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2023-06-03
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Growing Science
Resumen
Forest fires are a potential threat to life, as they contribute to reducing forest areas, impact on the
services we expect from ecosystems, the health of the inhabitants is affected by smoke and the
economic costs for the recovery of affected areas is high. The objective of the study is to apply
fuzzy logic to model the risk of forest fires in the Cajamarca-Peru region, incorporating variables
that represent biological, topographic, socioeconomic, and meteorological factors. The analysis
was based on the acquisition, editing and rasterization of the database, application of fuzzy
membership functions and image fuzzification, fuzzy superposition and spatial reclassification
of forest fire risk. The results obtained show that 71.68% of the area is under very low or medium
forest fire risk. However, 28.32% of the study area has a high to very high fire risk, which makes
the occurrence of fires susceptible to the lack of rain and water in the soil. It was found that
biological, topographic, and socioeconomic factors with their respective variables are directly
influenced by meteorological factor variables such as temperature, rainfall and water availability.
Fuzzy logic offered flexibility in modeling wildfire risk in the region, proving to be a useful tool
for predicting and mapping wildfire risk.
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forest fires risk, fuzzy logic, membership function, multi-criteria analysis, spatial modeling, vulnerability