Forest fire area detection using Sentinel-2 data: Case of the Beni Salah national forest ‒ Algeria

Rabah Zennir and Boubaker Khallef
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Rabah Zennir: Planning, Urban and Environmental Analysis Laboratory, Land Planning Department, Faculty of Earth Sciences, Badji Mokhtar-Annaba University, Annaba, Algeria
Boubaker Khallef: Department of Earth Sciences, Institute of Architecture and Earth Sciences, University Abbas Ferhat, Sétif, Algeria

Journal of Forest Science, 2023, vol. 69, issue 1, 33-40

Abstract: Forest cover plays an important role in terms of biodiversity and the environment. The Beni Salah national forest in its part which is located in the Guelma province in the extreme northeast of Algeria is an illustrative example where forest fires represent the chronic phenomenon which weighs heavily on this forest. The present study comes after a forest fire that occurred in 2021, when 3 000 ha of this forest were ravaged by forest fires according to the conservation of forests of Guelma. The main objective of this research is to map the severity of burns and estimate the severely burned area using Sentinel-2 satellite images based on remote sensing indices such as Normalized Difference Vegetation Index (NDVI), Differenced Normalized Difference Vegetation Index (dNDVI), Normalized Burn Ratio (NBR), Differenced Normalized Burn Ratio (dNBR), Green Normalized Difference Vegetation Index (GNDVI), Differenced Green Normalized Difference Vegetation Index (dGNDVI), Burn Area Index (BAI) and Relativized Burn Ratio (RBR). The result obtained revealed that 28.23% of the study area represents a seriously burned area. The established burn severity map is a real decision-making tool, but it still has certain limitations.

Keywords: burn severity; forest fires; remote sensing index; satellite image; state forest (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnljfs:v:69:y:2023:i:1:id:50-2022-jfs

DOI: 10.17221/50/2022-JFS

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