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

被引:0
作者
Zennir, Rabah [1 ]
Khallef, Boubaker [2 ]
机构
[1] Badji Mokhtar Annaba Univ, Fac Earth Sci, Land Planning Dept, Urban & Environm Anal Lab, Annaba, Algeria
[2] Univ Abbas Ferhat, Inst Architecture & Earth Sci, Dept Earth Sci, Setif, Algeria
关键词
burn severity; forest fires; remote sensing index; satellite image; state forest; SEVERITY;
D O I
暂无
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
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.
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页数:8
相关论文
共 19 条
[1]   A Review on Forest Fire Detection Techniques [J].
Alkhatib, Ahmad A. A. .
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2014,
[2]  
Bouhabila A., 2019, FORET ALGERIENNE FAC
[3]   SENTINEL 2 IMAGERY AND BURN RATIOS FOR ASSESSING THE JULY 5, 2021 WILDFIRES SEVERITY IN THE REGION OF KHENCHELA (NORTHEAST ALGERIA) [J].
Boulghobra, Nouar .
GEOGRAPHIA TECHNICA, 2021, 16 (02) :95-104
[4]  
Charfi G., 2016, CONTRIBUTION ANAL RE
[5]   Fire severity assessment by using NBR (Normalized Burn Ratio) and NDVI (Normalized Difference Vegetation Index) derived from LANDSAT TM/ETM images [J].
Escuin, S. ;
Navarro, R. ;
Fernandez, P. .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2008, 29 (04) :1053-1073
[6]  
Filipponi F., 2018, PROCEEDINGS, V2, DOI [10.3390/ecrs-2-05177, DOI 10.3390/ECRS-2-05177]
[7]   Field-Validated Burn-Severity Mapping in North Patagonian Forests [J].
Guadalupe Franco, Maria ;
Mundo, Ignacio A. ;
Veblen, Thomas T. .
REMOTE SENSING, 2020, 12 (02)
[8]  
Kurnaz B., 2020, Forest fire area detection by using Landsat-8 and Sentinel-2 satellite images: a case study in Mugla
[9]  
Kutter A., 2021, SUSTAINABLE FOREST M
[10]   The potentials of Sentinel-2 and LandSat-8 data in green infrastructure extraction, using object based image analysis (OBIA) method [J].
Labib, S. M. ;
Harris, Angela .
EUROPEAN JOURNAL OF REMOTE SENSING, 2018, 51 (01) :231-240