Determining the forest fire susceptibility map in the Astara city using the Analytical Hierarchy Process (AHP) and Frequency Ratio Model (FR)

In recent decades, intentional and unintentional forest fires have posed a serious threat to natural resources. These fires not only lead to direct human and financial losses but also contribute to the destruction of ecosystems, soil degradation, and loss of biodiversity. Additionally, they disrupt the balance of watersheds by reducing vegetation cover, increasing the risk of soil erosion, altering hydrological cycles, and ultimately affecting water quality and availability. Understanding fire-prone areas and their contributing factors is essential for effective fire management, risk reduction, and the development of preventive strategies. Fire risk mapping serves as a valuable tool for identifying critical areas and implementing targeted mitigation measures.

Fire risk mapping is an effective tool for identifying critical areas and mitigating fire hazards. This study evaluates the efficiency of the Geographic Information System (GIS), Analytical Hierarchy Process (AHP), and Frequency Ratio (FR) methods in mapping fire-prone areas in Astara, a city in western Gilan province covering 42,000 hectares. Astara is part of the Hyrcanian forests and has a humid climate with an average annual rainfall of 650 mm and a mean temperature of 13.1°C. In this study, the AHP method assigned weights to fire risk criteria based on expert surveys, while the FR method used the distribution of 70% of observed fire incidents. The obtained weights were applied to the study criteria to generate weighted maps. These maps were then integrated to produce a fire susceptibility map, categorizing fire risk into five classes, from very low to very high. To validate the results, 30% of recorded fire incidents and the ROC curve were used. The validation data were not included in the modeling phase.

In the AHP method, the consistency index (CI) was below 0.1, indicating reliable parameter selection. Model validation showed that the AHP method had an area under the curve (AUC) of 0.826, while the FR method achieved an AUC of 0.894. These results suggest that the FR model is more accurate for mapping fire-prone areas in Astara. The lower accuracy of the AHP model is likely due to potential errors in the pairwise comparison of criteria.Among the evaluated factors, proximity to villages (weight: 0.436) and roads (weight: 0.314) were the most influential in fire occurrence. In contrast, population density had the least impact (weight: 0.062).

In Astara, fires are concentrated in the northern and southeastern regions, particularly in watersheds No. 1, 4, and 7. The fire susceptibility map indicates that 1.82% of the study area is highly fire-prone, while 22.9% has moderate sensitivity. With proper management, fires in these areas can be controlled effectively. High-risk basins have a dense village distribution with short distances to roads, making them more susceptible to fires. Therefore, promoting public participation and equipping villagers with fire extinguishers can help prevent rapid fire spread.