IJEP 45(6): 510-526 : Vol. 45 Issue. 6 (June 2025)
Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology, Department of Chemistry, School of Science and Humanities, Chennai – 600 062, Tamil Nadu, India
Abstract
The purpose of this study is to simulate wildfires using the georaphical information system (GIS) method in Latakia Governorate, Syria, by merging different parameters, such as fuel danger index (FDI) as this index was calculated based on the specific vegetation type, normalized difference vegetation index (NDVI) and moisture content, normalized difference moisture index (NDMI), human activity danger index (ADI), weather danger index (WDI), topographic danger index (TDI) and fire severity assessment using the normalized burn ratio index (NBR) and differenced NBR (dNBR). The present research is on the Latakia governorate, located northeast of Syria. The FDI was evaluated based on vegetation type, density and moisture content and then unified under the term FDI by Raster calculator in GIS software. The ADI was estimated using the Euclidean distance tool in GIS software based on the proximity of the roads to the forest. The WDI elaborated on meteorological factors, like temperature, RH and wind speed using GIS software, such as the Kriging tool. The TDI included slope, aspect and elevation, modelled by GIS software relying on DEM. Meanwhile, dNBR is simulated by calculating NBR pre- and post-fire using Landsat data and GIS tools. The FDI rates from 2-26, with high and very high danger areas comprising around 60.6% of the total forest cover, mainly covered by conifer species (Pinus brutia) forests. The ADIr classes are from 320-4300, with high and very high-risk distributors over the whole forest region and the WDI categories are between 260-360. Then, TDI ranged between 0-5. The dNBR displayed the size of the fire from -895 to +1.120, with burned areas sited in medium and high severity classes. The work’s innovative aspects contain a complete and integrated strategy, use of advanced GIS-based modelling methods, focus on regional variations and provision of comprehensive data on metrics impacting wildfire ignition.
Keywords
Geographical information system, Remote sensing, Forest fire, Wildfire, Normalized difference vegetation index, Normalized difference moisture index, Differenced normalized burn ratio index
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