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<p>Wildfires significantly impact forest ecosystems, and climate change-driven extreme weather events, such as high temperatures, strong winds, and drought, are increasing both their frequency and severity. This study introduces a novel approach to wildfire risk assessment by incorporating Extreme Meteorological Conditions (EMC) into the recognized Multi-Criteria Decision Making (MCDM) method, the Analytical Hierarchy Process (AHP), within a Geographic Information Systems (GIS) environment supported by remote sensing data. The study area is Çanakkale Province, Türkiye, located within the Mediterranean Climate Zone, a region frequently affected large wildfires. Twelve criteria were selected within the AHP framework: one vegetation (forest areas), three topographic (slope, aspect, elevation), three anthropogenic (proximity to settlements, agricultural areas, and roads), and five climatic (air temperature, relative humidity, precipitation, wind speed, and Land Surface Temperature (LST)). Unlike previous studies that typically use Normal Climate Conditions (NCC), this study incorporates EMC. Wildfire risk was classified into five levels, ranging from very low (1) to very high (5). Both NCC and EMC analyses indicate that July is the highest-risk period, with moderate (3) and high-risk (4) zones dominating the area. The risk maps were validated using the Normalized Burn Ratio (NBR) index from Landsat satellite imagery, revealing that EMC-based analysis provides more accurate results. Furthermore, the increasing frequency and severity of EMCs are extending the fire season into autumn and spring. In conclusion, integrating EMCs into wildfire risk assessments highlights the urgent need to update disaster risk management plans, addressing climate change-driven vulnerability and ensuring more effective adaptation to future climate extremes.</p>

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Assessment of wildfire risk under normal and extreme climate conditions: A multi-criteria approach

  • 期刊论文

  • 发表日期：

    2026年3月11日

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  • Emre Özelkan,
  • Esra Eren,
  • Hasan Tatli,
  • Ramazan Cüneyt Erenoğlu

摘要

Wildfires significantly impact forest ecosystems, and climate change-driven extreme weather events, such as high temperatures, strong winds, and drought, are increasing both their frequency and severity. This study introduces a novel approach to wildfire risk assessment by incorporating Extreme Meteorological Conditions (EMC) into the recognized Multi-Criteria Decision Making (MCDM) method, the Analytical Hierarchy Process (AHP), within a Geographic Information Systems (GIS) environment supported by remote sensing data. The study area is Çanakkale Province, Türkiye, located within the Mediterranean Climate Zone, a region frequently affected large wildfires. Twelve criteria were selected within the AHP framework: one vegetation (forest areas), three topographic (slope, aspect, elevation), three anthropogenic (proximity to settlements, agricultural areas, and roads), and five climatic (air temperature, relative humidity, precipitation, wind speed, and Land Surface Temperature (LST)). Unlike previous studies that typically use Normal Climate Conditions (NCC), this study incorporates EMC. Wildfire risk was classified into five levels, ranging from very low (1) to very high (5). Both NCC and EMC analyses indicate that July is the highest-risk period, with moderate (3) and high-risk (4) zones dominating the area. The risk maps were validated using the Normalized Burn Ratio (NBR) index from Landsat satellite imagery, revealing that EMC-based analysis provides more accurate results. Furthermore, the increasing frequency and severity of EMCs are extending the fire season into autumn and spring. In conclusion, integrating EMCs into wildfire risk assessments highlights the urgent need to update disaster risk management plans, addressing climate change-driven vulnerability and ensuring more effective adaptation to future climate extremes.