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This study presents the first attempt in Sri Lanka to generate a forest fire risk map covering the entire country using a GIS-based forest fire index (FFI) model. The model utilized seven parameters: land use, temperature, slope, proximity to roads and settlements, elevation, and aspect. All these parameters were derived using GIS techniques with ArcGIS10.4 and QGIS3.16. Data from Remote Sensing sources, particularly the MODIS hotspot real-world dataset, were employed to gather fire count information for the year 2020. Validation was conducted through the merging hotspot technique and kernel density estimation (KDE). The research findings highlight the districts in the Central and Uva provinces, such as NuwaraEliya (10.3 km2), Kandy (2.74 km2), and Badulla (10.41 km2), as having a "very low risk" of forest fire potential. Conversely, districts like Hambanthota (0.1 km2), Kaluthara (0.04 km2), and Kurunegala (0.2 km2) exhibit a "very high risk" of forest fire potential, although it is negligible compared country's total area. Overall, the study suggests that Sri Lanka is not currently facing a significant threat of forest fires and is a "medium risk" of forest fires as 49.49% of land falls under this category. These results are of immense value to relevant authorities, including the Ministry of Wildlife and Forest Resources Conservation, in formulating effective strategies to manage and mitigate forest fire risks in the country.
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Randika K. Makumbura
Institute of Technology Sligo
Prasad Dissanayake
University of Wollongong
Miyuru B. Gunathilake
Norwegian Institute of Bioeconomy Research
Case Studies in Chemical and Environmental Engineering
The University of Tokyo
University of Oulu
University of Wollongong
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Makumbura et al. (Mon,) studied this question.
synapsesocial.com/papers/68e75c84b6db6435876d30da — DOI: https://doi.org/10.1016/j.cscee.2024.100680
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