Abstract
Forest fires result in a range of adverse Earth's eco-environment and economic impacts. It is crucial to timely and accurately assess the severity of a forest fire, because burn severity is the factor for post-fire vegetation recovery. On the 7th July 2015, a forest fire occurred in western Spain, Comunidad Valenciana, near the villages of Montán and Caudiel. The fire mainly affected low vegetation types such as scrublands and herbs. This study intended to evaluate the use of Sentinel-2 data for identifying burn severity within areas covered by low vegetation, with the single band, spectral index, and differential spectral index Sentinel-2 data assessed. The results confirmed that the use of near-infrared and short-wave infrared ranges of Sentinel-2 data was suitable for identifying burned and unburned areas of low vegetation. The use of the normalized difference vegetation index performed best in distinguishing between areas of highly and moderately damaged vegetation, whereas the use of the normalized burn ratio (NBR) and NBR2 performed best for distinguishing between areas of completely destroyed and moderately damaged vegetation. These preliminary research results indicated that Sentinel-2 data are useful for forest fire monitoring in areas with low vegetation.
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This work was supported by the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi (Grant No. 2020L0751). Thank Copernicus Emergency Management Service for the public information and data. We are grateful to the anonymous reviewers for providing comments and suggestions that greatly improved the article.
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Luo, H., Wu, J. An Assessment of the Suitability of Sentinel-2 Data for Identifying Burn Severity in Areas of Low Vegetation. J Indian Soc Remote Sens 50, 1135–1144 (2022). https://doi.org/10.1007/s12524-022-01518-7
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DOI: https://doi.org/10.1007/s12524-022-01518-7