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

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...

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Bibliographic Details
Main Authors: Abdo, H.G (Author), Al Dughairi, A.A (Author), Almohamad, H. (Author), Al-Mutiry, M. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Online Access:View Fulltext in Publisher
LEADER 02700nam a2200217Ia 4500
001 10.3390-su14084668
008 220517s2022 CNT 000 0 und d
020 |a 20711050 (ISSN) 
245 1 0 |a GIS-Based Frequency Ratio and Analytic Hierarchy Process for Forest Fire Susceptibility Mapping in the Western Region of Syria 
260 0 |b MDPI  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.3390/su14084668 
520 3 |a 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. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. 
650 0 4 |a analytic hierarchy process 
650 0 4 |a forest fire susceptibility 
650 0 4 |a frequency ratio 
650 0 4 |a Syria 
700 1 |a Abdo, H.G.  |e author 
700 1 |a Al Dughairi, A.A.  |e author 
700 1 |a Almohamad, H.  |e author 
700 1 |a Al-Mutiry, M.  |e author 
773 |t Sustainability (Switzerland)