Generation of forest fire risk maps using geographic information systems and remote sensing techniques

Forest fires are natural disasters that lead to the disruption of ecological balance, a reduction in biodiversity, and significant harm to human life and economic activities. This situation necessitates conducting forest fire risk analyses based on scientific foundations and developing spatial models that will guide decision-makers. In this study, a holistic model for identifying areas at risk of forest fires was developed using Geographic Information Systems (GIS), remote sensing technologies, and the widely used Weighted Overlay Method (WOM) approach from multi-criteria decision-making techniques. In the selected study area, six different criteria were evaluated: slope, land use, vegetation (NDVI), proximity to roads, population density, and fire history location data. As a result of the analyses conducted in the GIS environment, the risk map created showed an 85.3% overlap with past fire data, demonstrating the reliability of the model. This comprehensive approach enhances the effectiveness of decision support systems in forest fire management processes and provides significant contributions to sustainable forest and environmental management.