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A Multi-Criteria Forest Fire Danger Assessment System on GIS Using Literature-Based Model and Analytical Hierarchy Process Model for Mediterranean Coast of Manavgat, Türkiye

Author

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  • İzzet Ersoy

    (Department of Geomatics Engineering, Sivas Cumhuriyet University, Sivas 58140, Türkiye)

  • Emre Ünsal

    (Department of Software Engineering, Sivas Cumhuriyet University, Sivas 58140, Türkiye)

  • Önder Gürsoy

    (Department of Geomatics Engineering, Sivas Cumhuriyet University, Sivas 58140, Türkiye)

Abstract

Forest fires pose significant environmental and economic risks, particularly in fire-prone regions like the Mediterranean coast of Türkiye. This study presents a comprehensive Forest Fire Danger Assessment System (FoFiDAS), by integrating Geographic Information Systems (GIS), a literature-based model, the Analytical Hierarchy Process (AHP), and machine learning (ML) to improve forest fire danger classification. Both models integrate 13 key parameters identified through the literature. A comparison of these models revealed 53% overlap in fire danger classifications. While the AHP model, based on expert-weighted assessment, provided a more structured and localized classification, the literature-based model relied on broader scientific data but lacked adaptability. Pearson correlation analysis demonstrated a strong correlation between fire danger classifications and historical fire occurrences, with correlation scores of 0.927 (AHP) and 0.939 (literature-based). Further ROC analysis confirmed the predictive performance of both models, yielding AUC values of 0.91 and 0.9121 for the literature-based and AHP models, respectively. Five ML algorithms were used to validate classification performances, with Artificial Neural Network (ANN) achieving the highest accuracy (86.5%). The accuracy of the ANN algorithm exceeded 0.93 for each danger class, and the F1-Score was above 0.85. FoFiDAS offers a reliable tool for fire danger assessment, supporting early intervention and decision making.

Suggested Citation

  • İzzet Ersoy & Emre Ünsal & Önder Gürsoy, 2025. "A Multi-Criteria Forest Fire Danger Assessment System on GIS Using Literature-Based Model and Analytical Hierarchy Process Model for Mediterranean Coast of Manavgat, Türkiye," Sustainability, MDPI, vol. 17(5), pages 1-27, February.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:5:p:1971-:d:1599459
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    References listed on IDEAS

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    1. Hamed Adab & Kasturi Kanniah & Karim Solaimani, 2013. "Modeling forest fire risk in the northeast of Iran using remote sensing and GIS techniques," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(3), pages 1723-1743, February.
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