Articles | Volume 18, issue 2
https://doi.org/10.5194/os-18-361-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-18-361-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Mar 2022
Research article |
| 24 Mar 2022
| 24 Mar 2022
The capabilities of Sentinel-MSI (2A/2B) and Landsat-OLI (8/9) in seagrass and algae species differentiation using spectral reflectance
Abderrazak Bannari
CORRESPONDING AUTHOR
Space Pix-Map International Inc., Gatineau, Québec, J8R 3R7,
Canada
Thamer Salim Ali
Department of Natural Resources and Environment, College of
Graduate Studies, Arabian Gulf University, P.O. Box 26671, Manama, Kingdom of Bahrain
Asma Abahussain
Department of Natural Resources and Environment, College of
Graduate Studies, Arabian Gulf University, P.O. Box 26671, Manama, Kingdom of Bahrain
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Cited
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- A novel deep learning algorithm for broad scale seagrass extent mapping in shallow coastal environments J. Peng et al. 10.1016/j.isprsjprs.2024.12.008
- Environmental Impacts of Aquaculture in the Philippines A. Tahiluddin et al. 10.46989/001c.133778
- Seagrass Carbon Stocks And Sequestration In Habitat Impacted By Tin Mining Activities In Bangka Belitung, Indonesia W. Adi et al. 10.24057/2071-9388-2025-3459
- Comparing the Capability of Sentinel-2 and Landsat 9 Imagery for Mapping Water and Sandbars in the River Bed of the Lower Tagus River (Portugal) R. Gerardo & I. de Lima 10.3390/rs15071927
- Technology for environmental management in Small Island Developing States: the case of Bahrain H. Naser 10.1016/j.cosust.2022.101219
- Multi-Temporal Satellite Investigation of gas Flaring in Iraq and Iran: The DAFI Porting on Collection 2 Landsat 8/9 and Sentinel 2A/B M. Faruolo et al. 10.3390/s23125734
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- Remote-Sensing Indicators and Methods for Coastal-Ecosystem Health Assessment: A Review of Progress, Challenges, and Future Directions L. Zhao et al. 10.3390/w17131971
- Optimal locating satellite observation reaches for manning’s equation: From surface water and ocean topography mission river Database Q. Liu et al. 10.1016/j.jhydrol.2025.132849
- Mapping the National Seagrass Extent in Seychelles Using PlanetScope NICFI Data C. Lee et al. 10.3390/rs15184500
- Discriminating Seagrasses from Green Macroalgae in European Intertidal Areas Using High-Resolution Multispectral Drone Imagery S. Oiry et al. 10.3390/rs16234383
- Mapping subtidal seagrass in the turbid Baltic Sea: Rethinking satellite sensor selection using a sensor-agnostic pipeline E. Schütt et al. 10.1016/j.srs.2025.100243
- Subtidal seagrass and blue carbon mapping at the regional scale: a cloud-native multi-temporal Earth Observation approach M. Roca et al. 10.1080/15481603.2024.2438838
- Selecting the best habitat mapping technique: a comparative assessment for fisheries management in Exmouth Gulf S. Evans et al. 10.3389/fmars.2025.1570277
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- A multidirectional pairwise coupling approach with spectral features unmixing to quantify total phosphorus, total nitrogen, and chlorophyll-a in urban rivers Y. Zhang & Z. Yang 10.1016/j.jhazmat.2024.135174
17 citations as recorded by crossref.
- Improving Ocean Management Using Insights from Space D. McCauley et al. 10.1146/annurev-marine-050823-120619
- A novel deep learning algorithm for broad scale seagrass extent mapping in shallow coastal environments J. Peng et al. 10.1016/j.isprsjprs.2024.12.008
- Environmental Impacts of Aquaculture in the Philippines A. Tahiluddin et al. 10.46989/001c.133778
- Seagrass Carbon Stocks And Sequestration In Habitat Impacted By Tin Mining Activities In Bangka Belitung, Indonesia W. Adi et al. 10.24057/2071-9388-2025-3459
- Comparing the Capability of Sentinel-2 and Landsat 9 Imagery for Mapping Water and Sandbars in the River Bed of the Lower Tagus River (Portugal) R. Gerardo & I. de Lima 10.3390/rs15071927
- Technology for environmental management in Small Island Developing States: the case of Bahrain H. Naser 10.1016/j.cosust.2022.101219
- Multi-Temporal Satellite Investigation of gas Flaring in Iraq and Iran: The DAFI Porting on Collection 2 Landsat 8/9 and Sentinel 2A/B M. Faruolo et al. 10.3390/s23125734
- Seagrasses on the move: Tracing the multi-decadal species distribution trends in lagoon meadows using Landsat imagery P. Cingano et al. 10.1016/j.ecoinf.2024.102685
- Remote-Sensing Indicators and Methods for Coastal-Ecosystem Health Assessment: A Review of Progress, Challenges, and Future Directions L. Zhao et al. 10.3390/w17131971
- Optimal locating satellite observation reaches for manning’s equation: From surface water and ocean topography mission river Database Q. Liu et al. 10.1016/j.jhydrol.2025.132849
- Mapping the National Seagrass Extent in Seychelles Using PlanetScope NICFI Data C. Lee et al. 10.3390/rs15184500
- Discriminating Seagrasses from Green Macroalgae in European Intertidal Areas Using High-Resolution Multispectral Drone Imagery S. Oiry et al. 10.3390/rs16234383
- Mapping subtidal seagrass in the turbid Baltic Sea: Rethinking satellite sensor selection using a sensor-agnostic pipeline E. Schütt et al. 10.1016/j.srs.2025.100243
- Subtidal seagrass and blue carbon mapping at the regional scale: a cloud-native multi-temporal Earth Observation approach M. Roca et al. 10.1080/15481603.2024.2438838
- Selecting the best habitat mapping technique: a comparative assessment for fisheries management in Exmouth Gulf S. Evans et al. 10.3389/fmars.2025.1570277
- Comparison of Lake Area Extraction Algorithms in Qinghai Tibet Plateau Leveraging Google Earth Engine and Landsat-9 Data X. Li et al. 10.3390/rs14184612
- A multidirectional pairwise coupling approach with spectral features unmixing to quantify total phosphorus, total nitrogen, and chlorophyll-a in urban rivers Y. Zhang & Z. Yang 10.1016/j.jhazmat.2024.135174
Latest update: 07 Jul 2025
Short summary
Spectral analyses showed the importance of the blue, green, and NIR wavelengths for submerged aquatic vegetation (SAV) discrimination. Moreover, the integration of the blue or the green bands in water vegetation indices (WVIs) increases their discriminating power of SAV. Statistical fits between homologous bands of Sentinel-SMI and Landsat-OLI revealed excellent linear relationships (R2 of 0.999) with insignificant RMSD (≤ 0.0015). Accordingly, MSI and OLI sensors are spectrally similar.
Spectral analyses showed the importance of the blue, green, and NIR wavelengths for submerged...
