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GIS-Based Frequency Ratio and Analytic Hierarchy Process for Forest Fire Susceptibility Mapping in the Western Region of Syria

Author

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  • Hazem Ghassan Abdo

    (Geography Department, Faculty of Arts and Humanities, University of Tartous, Tartous P.O. Box 2147, Syria
    Geography Department, Faculty of Arts and Humanities, University of Damascus, Damascus P.O. Box 30621, Syria
    Geography Department, Faculty of Arts and Humanities, University of Tishreen, Lattakia P.O. Box 2237, Syria)

  • Hussein Almohamad

    (Department of Geography, College of Arabic Language and Social Studies, Qassim University, Buraydah 51452, Saudi Arabia)

  • Ahmed Abdullah Al Dughairi

    (Department of Geography, College of Arabic Language and Social Studies, Qassim University, Buraydah 51452, Saudi Arabia)

  • Motirh Al-Mutiry

    (Department of Geography, College of Arts, Princess Nourah Bint Abdulrahman University, Riyadh 11671, Saudi Arabia)

Abstract

Forest fires are among the most major causes of global ecosystem degradation. The integration of spatial information from various sources using statistical analyses in the GIS environment is an original tool in managing the spread of forest fires, which is one of the most significant natural hazards in the western region of Syria. Moreover, the western region of Syria is characterized by a significant lack of data to assess forest fire susceptibility as one of the most significant consequences of the current war. This study aimed to conduct a performance comparison of frequency ratio (FR) and analytic hierarchy process (AHP) techniques in delineating the spatial distribution of forest fire susceptibility in the Al-Draikich region, located in the western region of Syria. An inventory map of historical forest fire events was produced by spatially digitizing 32 fire incidents during the summers of 2019, 2020, and 2021. The forest fire events were divided into a training dataset with 70% (22 events) and a test dataset with 30% (10 events). Subsequently, FR and AHP techniques were used to associate the training data set with the 13 driving factors: slope, aspect, curvature, elevation, Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Topographic Wetness Index (TWI), rainfall, temperature, wind speed, TWI, and distance to settlements, rivers and roads. The accuracy of the maps resulting from the modeling process was checked using the validation dataset and receiver operating characteristics (ROC) curves with the area under the curve (AUC). The FR method with AUC = 0.864 achieved the highest value compared to the AHP method with AUC = 0.838. The outcomes of this assessment provide constructive spatial insights for adopting forest management strategies in the study area, especially in light of the consequences of the current war.

Suggested Citation

  • Hazem Ghassan Abdo & Hussein Almohamad & Ahmed Abdullah Al Dughairi & Motirh Al-Mutiry, 2022. "GIS-Based Frequency Ratio and Analytic Hierarchy Process for Forest Fire Susceptibility Mapping in the Western Region of Syria," Sustainability, MDPI, vol. 14(8), pages 1-20, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:8:p:4668-:d:793297
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    1. Bijay Halder & Papiya Banik & Hussein Almohamad & Ahmed Abdullah Al Dughairi & Motrih Al-Mutiry & Haya Falah Al Shahrani & Hazem Ghassan Abdo, 2022. "Land Suitability Investigation for Solar Power Plant Using GIS, AHP and Multi-Criteria Decision Approach: A Case of Megacity Kolkata, West Bengal, India," Sustainability, MDPI, vol. 14(18), pages 1-21, September.

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