Articles | Volume 10, issue 3
https://doi.org/10.5194/essd-10-1439-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-10-1439-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The SeaSWIR dataset
Flemish Institute for Technological Research (VITO), Mol, 2400,
Belgium
David Doxaran
Laboratoire d'Océanographie de Villefranche (LOV),
Villefranche-sur-Mer, 06230, UMR 7093, CNRS/Sorbonne Université, France
Ana Dogliotti
Instituto de Astronomía y Física del Espacio (IAFE),
C1428ZAA, CONICET/UBA, Argentina
Bouchra Nechad
Royal Belgian Institute for Natural Sciences (RBINS), Operational
Directorate Natural Environments, Brussels, 1200, Belgium
Kevin Ruddick
Royal Belgian Institute for Natural Sciences (RBINS), Operational
Directorate Natural Environments, Brussels, 1200, Belgium
Dries Raymaekers
Flemish Institute for Technological Research (VITO), Mol, 2400,
Belgium
Sindy Sterckx
Flemish Institute for Technological Research (VITO), Mol, 2400,
Belgium
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Cited
13 citations as recorded by crossref.
- Global Estimation of Suspended Particulate Matter From Satellite Ocean Color Imagery J. Wei et al. 10.1029/2021JC017303
- An Algorithm to Estimate Suspended Particulate Matter Concentrations and Associated Uncertainties from Remote Sensing Reflectance in Coastal Environments J. Tavora et al. 10.3390/rs12132172
- Retrieval and Validation of Water Turbidity at Metre-Scale Using Pléiades Satellite Data: A Case Study in the Gironde Estuary Y. Luo et al. 10.3390/rs12060946
- Water properties in the La Plata River Estuary from VIIRS observations W. Shi & M. Wang 10.1016/j.csr.2020.104100
- Using Optical Water Types to Monitor Changes in Optically Complex Inland and Coastal Waters K. Uudeberg et al. 10.3390/rs11192297
- An empirical algorithm to seamlessly retrieve the concentration of suspended particulate matter from water color across ocean to turbid river mouths X. Yu et al. 10.1016/j.rse.2019.111491
- Spectral reflectance of marine macroplastics in the VNIR and SWIR measured in a controlled environment M. Moshtaghi et al. 10.1038/s41598-021-84867-6
- Evaluation of Atmospheric Correction Algorithms for Sentinel-2-MSI and Sentinel-3-OLCI in Highly Turbid Estuarine Waters P. Renosh et al. 10.3390/rs12081285
- Estimating ultraviolet reflectance from visible bands in ocean colour remote sensing H. Liu et al. 10.1016/j.rse.2021.112404
- Remotely estimating total suspended solids concentration in clear to extremely turbid waters using a novel semi-analytical method D. Jiang et al. 10.1016/j.rse.2021.112386
- Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3 N. Pahlevan et al. 10.1016/j.rse.2021.112860
- Living up to the Hype of Hyperspectral Aquatic Remote Sensing: Science, Resources and Outlook H. Dierssen et al. 10.3389/fenvs.2021.649528
- Robust algorithm for estimating total suspended solids (TSS) in inland and nearshore coastal waters S. Balasubramanian et al. 10.1016/j.rse.2020.111768
13 citations as recorded by crossref.
- Global Estimation of Suspended Particulate Matter From Satellite Ocean Color Imagery J. Wei et al. 10.1029/2021JC017303
- An Algorithm to Estimate Suspended Particulate Matter Concentrations and Associated Uncertainties from Remote Sensing Reflectance in Coastal Environments J. Tavora et al. 10.3390/rs12132172
- Retrieval and Validation of Water Turbidity at Metre-Scale Using Pléiades Satellite Data: A Case Study in the Gironde Estuary Y. Luo et al. 10.3390/rs12060946
- Water properties in the La Plata River Estuary from VIIRS observations W. Shi & M. Wang 10.1016/j.csr.2020.104100
- Using Optical Water Types to Monitor Changes in Optically Complex Inland and Coastal Waters K. Uudeberg et al. 10.3390/rs11192297
- An empirical algorithm to seamlessly retrieve the concentration of suspended particulate matter from water color across ocean to turbid river mouths X. Yu et al. 10.1016/j.rse.2019.111491
- Spectral reflectance of marine macroplastics in the VNIR and SWIR measured in a controlled environment M. Moshtaghi et al. 10.1038/s41598-021-84867-6
- Evaluation of Atmospheric Correction Algorithms for Sentinel-2-MSI and Sentinel-3-OLCI in Highly Turbid Estuarine Waters P. Renosh et al. 10.3390/rs12081285
- Estimating ultraviolet reflectance from visible bands in ocean colour remote sensing H. Liu et al. 10.1016/j.rse.2021.112404
- Remotely estimating total suspended solids concentration in clear to extremely turbid waters using a novel semi-analytical method D. Jiang et al. 10.1016/j.rse.2021.112386
- Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3 N. Pahlevan et al. 10.1016/j.rse.2021.112860
- Living up to the Hype of Hyperspectral Aquatic Remote Sensing: Science, Resources and Outlook H. Dierssen et al. 10.3389/fenvs.2021.649528
- Robust algorithm for estimating total suspended solids (TSS) in inland and nearshore coastal waters S. Balasubramanian et al. 10.1016/j.rse.2020.111768
Latest update: 27 May 2023
Short summary
The SeaSWIR dataset consists of 137 ASD marine reflectances, 137 total suspended matter (TSM) measurements and 97 turbidity measurements gathered at three turbid estuarine sites (Gironde, La Plata, Scheldt). The dataset is valuable because of the high-quality measurements of the marine reflectance in the Short Wave InfraRed I region (SWIR-I: 1000–1200 nm) and SWIR-II (1200–1300 nm) and because of the wide range of TSM concentrations from 48 mg L−1 up to 1400 mg L−1.
The SeaSWIR dataset consists of 137 ASD marine reflectances, 137 total suspended matter (TSM)...