Recently, increasing forest fires have contributed to deforestation and desertification in the Hyrcanian forests in northern Iran. It is crucial to consider the complex interactions of forest fires with particularities of the environment and the social and economic factors. This study introduces a conceptual approach to developing a comprehensive forest fire vulnerability index using both quantitative and qualitative methods. The indicators can be grouped into the three components of vulnerability (exposure, sensitivity, and adaptive capacity) based on three categories (social, economic, and environmental), resulting in three indexes: Forest Fire Exposure Index (FEI), Forest Fire Sensitivity Index (FSI) and Forest Fire Adaptive Capacity Index (FACI). Finally, we can create an integrated Forest Fire Vulnerability Index (FVI). The most vulnerable areas to forest fires can be mapped using remote sensing data, geographic information systems (GIS), the statistical data available at the Forests, Range & Watershed Management Organization (FRWO), and machine learning models. By localizing the input data and socio-economic indicators, the methodology is transferrable to other regions and helps forest fire management and prevention planning.

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