Cite Article

Characterization of Fire Severity in the Moroccan Rif Using Landsat-8 and Sentinel-2 Satellite Images

Choose citation format

BibTeX

@article{IJASEIT10342,
   author = {Issam Eddine Zidane and Rachid Lhissou and Maryem Ismaili and Yassine Manyari and Abdelali Bouli and Mustapha Mabrouki},
   title = {Characterization of Fire Severity in the Moroccan Rif Using Landsat-8 and Sentinel-2 Satellite Images},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {11},
   number = {1},
   year = {2021},
   pages = {72--83},
   keywords = {Sentinel-2 MSI; Landsat-8 OLI; forest fires mapping; NBR; BAI; spectral indices; Morocco.},
   abstract = {Forest ecosystems are exposed increasingly to a variety of human activities and accentuated by climate change. With its Mediterranean climate, Northern Morocco is very hot, which exposes forests to widespread fires. This work aims at the delineation of wildfires and the spectral characterization of burnt vegetation as well as the characterization of the fire severity in the North of Morocco by using Landsat-8, Sentinel-2 spectral data, and topographic data. The methods used include the derivation of wildfires spectral indices and the computation of topographic parameters (elevation, slope, exposure) from SRTM and PALSAR digital elevation models. Then, the Spectral Angle Mapper (SAM) classification was used to map forest fires' severity. Furthermore, we have compared the severity classes obtained from the SAM method applied to Landsat 8 and Sentinel 2 data, with different spectral indices specialized in detecting wildfires, on the one hand, and topographic data, on the other hand. Results showed that MIRBI and NBR indices allow a better characterization of burned areas than BAI index. For its part, SAM classification provides a fair characterization of the severity classes of burnt forests. It has also been shown that the MIRBI index and sun exposure are strongly correlated with severity classes. The obtained maps show the spatial heterogeneity of burns severity and how they interact with topography. These maps may help land resource managers and fire officials predict areas of potential fire hazards and study vegetation regrowth areas after fires.},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10342},
   doi = {10.18517/ijaseit.11.1.10342}
}

EndNote

%A Zidane, Issam Eddine
%A Lhissou, Rachid
%A Ismaili, Maryem
%A Manyari, Yassine
%A Bouli, Abdelali
%A Mabrouki, Mustapha
%D 2021
%T Characterization of Fire Severity in the Moroccan Rif Using Landsat-8 and Sentinel-2 Satellite Images
%B 2021
%9 Sentinel-2 MSI; Landsat-8 OLI; forest fires mapping; NBR; BAI; spectral indices; Morocco.
%! Characterization of Fire Severity in the Moroccan Rif Using Landsat-8 and Sentinel-2 Satellite Images
%K Sentinel-2 MSI; Landsat-8 OLI; forest fires mapping; NBR; BAI; spectral indices; Morocco.
%X Forest ecosystems are exposed increasingly to a variety of human activities and accentuated by climate change. With its Mediterranean climate, Northern Morocco is very hot, which exposes forests to widespread fires. This work aims at the delineation of wildfires and the spectral characterization of burnt vegetation as well as the characterization of the fire severity in the North of Morocco by using Landsat-8, Sentinel-2 spectral data, and topographic data. The methods used include the derivation of wildfires spectral indices and the computation of topographic parameters (elevation, slope, exposure) from SRTM and PALSAR digital elevation models. Then, the Spectral Angle Mapper (SAM) classification was used to map forest fires' severity. Furthermore, we have compared the severity classes obtained from the SAM method applied to Landsat 8 and Sentinel 2 data, with different spectral indices specialized in detecting wildfires, on the one hand, and topographic data, on the other hand. Results showed that MIRBI and NBR indices allow a better characterization of burned areas than BAI index. For its part, SAM classification provides a fair characterization of the severity classes of burnt forests. It has also been shown that the MIRBI index and sun exposure are strongly correlated with severity classes. The obtained maps show the spatial heterogeneity of burns severity and how they interact with topography. These maps may help land resource managers and fire officials predict areas of potential fire hazards and study vegetation regrowth areas after fires.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10342
%R doi:10.18517/ijaseit.11.1.10342
%J International Journal on Advanced Science, Engineering and Information Technology
%V 11
%N 1
%@ 2088-5334

IEEE

Issam Eddine Zidane,Rachid Lhissou,Maryem Ismaili,Yassine Manyari,Abdelali Bouli and Mustapha Mabrouki,"Characterization of Fire Severity in the Moroccan Rif Using Landsat-8 and Sentinel-2 Satellite Images," International Journal on Advanced Science, Engineering and Information Technology, vol. 11, no. 1, pp. 72-83, 2021. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.11.1.10342.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Zidane, Issam Eddine
AU  - Lhissou, Rachid
AU  - Ismaili, Maryem
AU  - Manyari, Yassine
AU  - Bouli, Abdelali
AU  - Mabrouki, Mustapha
PY  - 2021
TI  - Characterization of Fire Severity in the Moroccan Rif Using Landsat-8 and Sentinel-2 Satellite Images
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 11 (2021) No. 1
Y2  - 2021
SP  - 72
EP  - 83
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - Sentinel-2 MSI; Landsat-8 OLI; forest fires mapping; NBR; BAI; spectral indices; Morocco.
N2  - Forest ecosystems are exposed increasingly to a variety of human activities and accentuated by climate change. With its Mediterranean climate, Northern Morocco is very hot, which exposes forests to widespread fires. This work aims at the delineation of wildfires and the spectral characterization of burnt vegetation as well as the characterization of the fire severity in the North of Morocco by using Landsat-8, Sentinel-2 spectral data, and topographic data. The methods used include the derivation of wildfires spectral indices and the computation of topographic parameters (elevation, slope, exposure) from SRTM and PALSAR digital elevation models. Then, the Spectral Angle Mapper (SAM) classification was used to map forest fires' severity. Furthermore, we have compared the severity classes obtained from the SAM method applied to Landsat 8 and Sentinel 2 data, with different spectral indices specialized in detecting wildfires, on the one hand, and topographic data, on the other hand. Results showed that MIRBI and NBR indices allow a better characterization of burned areas than BAI index. For its part, SAM classification provides a fair characterization of the severity classes of burnt forests. It has also been shown that the MIRBI index and sun exposure are strongly correlated with severity classes. The obtained maps show the spatial heterogeneity of burns severity and how they interact with topography. These maps may help land resource managers and fire officials predict areas of potential fire hazards and study vegetation regrowth areas after fires.
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10342
DO  - 10.18517/ijaseit.11.1.10342

RefWorks

RT Journal Article
ID 10342
A1 Zidane, Issam Eddine
A1 Lhissou, Rachid
A1 Ismaili, Maryem
A1 Manyari, Yassine
A1 Bouli, Abdelali
A1 Mabrouki, Mustapha
T1 Characterization of Fire Severity in the Moroccan Rif Using Landsat-8 and Sentinel-2 Satellite Images
JF International Journal on Advanced Science, Engineering and Information Technology
VO 11
IS 1
YR 2021
SP 72
OP 83
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 Sentinel-2 MSI; Landsat-8 OLI; forest fires mapping; NBR; BAI; spectral indices; Morocco.
AB Forest ecosystems are exposed increasingly to a variety of human activities and accentuated by climate change. With its Mediterranean climate, Northern Morocco is very hot, which exposes forests to widespread fires. This work aims at the delineation of wildfires and the spectral characterization of burnt vegetation as well as the characterization of the fire severity in the North of Morocco by using Landsat-8, Sentinel-2 spectral data, and topographic data. The methods used include the derivation of wildfires spectral indices and the computation of topographic parameters (elevation, slope, exposure) from SRTM and PALSAR digital elevation models. Then, the Spectral Angle Mapper (SAM) classification was used to map forest fires' severity. Furthermore, we have compared the severity classes obtained from the SAM method applied to Landsat 8 and Sentinel 2 data, with different spectral indices specialized in detecting wildfires, on the one hand, and topographic data, on the other hand. Results showed that MIRBI and NBR indices allow a better characterization of burned areas than BAI index. For its part, SAM classification provides a fair characterization of the severity classes of burnt forests. It has also been shown that the MIRBI index and sun exposure are strongly correlated with severity classes. The obtained maps show the spatial heterogeneity of burns severity and how they interact with topography. These maps may help land resource managers and fire officials predict areas of potential fire hazards and study vegetation regrowth areas after fires.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10342
DO  - 10.18517/ijaseit.11.1.10342