Articles | Volume 14, issue 6
https://doi.org/10.5194/essd-14-2697-2022
© 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/essd-14-2697-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Optical and biogeochemical properties of diverse Belgian inland and coastal waters
Alexandre Castagna
CORRESPONDING AUTHOR
Protistology and Aquatic Ecology, Ghent University, Ghent, Belgium
Luz Amadei Martínez
Protistology and Aquatic Ecology, Ghent University, Ghent, Belgium
Margarita Bogorad
Protistology and Aquatic Ecology, Ghent University, Ghent, Belgium
Ilse Daveloose
Protistology and Aquatic Ecology, Ghent University, Ghent, Belgium
Renaat Dasseville
Protistology and Aquatic Ecology, Ghent University, Ghent, Belgium
Heidi Melita Dierssen
Department of Marine Sciences, University of Connecticut, Groton, CT, United States
Matthew Beck
Operational Directorate Natural Environment, Royal Belgian Institute of Natural Sciences, Brussels, Belgium
Jonas Mortelmans
Marine Observation Centre (MOC), Flanders Marine Instute (VLIZ), Oostende, Belgium
Héloïse Lavigne
Operational Directorate Natural Environment, Royal Belgian Institute of Natural Sciences, Brussels, Belgium
Ana Dogliotti
Instituto de Astronomía y Física del Espacio (IAFE), CONICET-Universidad de Buenos Aires, Buenos Aires, Argentina
David Doxaran
Laboratoire d'Océanographie de Villefranche, CNRS-Sorbonne University, Villefranche, France
Kevin Ruddick
Operational Directorate Natural Environment, Royal Belgian Institute of Natural Sciences, Brussels, Belgium
Wim Vyverman
Protistology and Aquatic Ecology, Ghent University, Ghent, Belgium
Koen Sabbe
Protistology and Aquatic Ecology, Ghent University, Ghent, Belgium
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Cited
14 citations as recorded by crossref.
- In-situ optical water quality monitoring sensors—applications, challenges, and future opportunities M. Kumar et al. 10.3389/frwa.2024.1380133
- Bio-geo-optical modelling of natural waters S. Bi et al. 10.3389/fmars.2023.1196352
- The HYPERMAQ dataset: bio-optical properties of moderately to extremely turbid waters H. Lavigne et al. 10.5194/essd-14-4935-2022
- Bio-optical properties of the cyanobacterium Nodularia spumigena S. Garaba et al. 10.5194/essd-15-4163-2023
- Monitoring of high biomass Phaeocystis globosa blooms in the Southern North Sea by in situ and future spaceborne hyperspectral radiometry H. Lavigne et al. 10.1016/j.rse.2022.113270
- An Evaluation of Sun-Glint Correction Methods for UAV-Derived Secchi Depth Estimations in Inland Water Bodies E. Tiškus et al. 10.3390/drones7090546
- Remote Sensing Retrieval of Water Clarity in Clear Oceanic to Extremely Turbid Coastal Waters From Multiple Spaceborne Sensors J. Xiang et al. 10.1109/TGRS.2023.3318590
- Evaluation of historic and new detection algorithms for different types of plastics over land and water from hyperspectral data and imagery A. Castagna et al. 10.1016/j.rse.2023.113834
- Towards global long-term water transparency products from the Landsat archive D. Maciel et al. 10.1016/j.rse.2023.113889
- Chromaticity-Based Discrimination of Algal Bloom from Inland and Coastal Waters Using In Situ Hyperspectral Remote Sensing Reflectance D. Zhao et al. 10.3390/w16162276
- Variability of light absorption coefficients by different size fractions of suspensions in the southern Baltic Sea J. Meler et al. 10.5194/bg-20-2525-2023
- Holistic optical water type classification for ocean, coastal, and inland waters S. Bi & M. Hieronymi 10.1002/lno.12606
- Evaluation of eight band SuperDove imagery for aquatic applications Q. Vanhellemont 10.1364/OE.483418
- Optical and biogeochemical properties of diverse Belgian inland and coastal waters A. Castagna et al. 10.5194/essd-14-2697-2022
13 citations as recorded by crossref.
- In-situ optical water quality monitoring sensors—applications, challenges, and future opportunities M. Kumar et al. 10.3389/frwa.2024.1380133
- Bio-geo-optical modelling of natural waters S. Bi et al. 10.3389/fmars.2023.1196352
- The HYPERMAQ dataset: bio-optical properties of moderately to extremely turbid waters H. Lavigne et al. 10.5194/essd-14-4935-2022
- Bio-optical properties of the cyanobacterium Nodularia spumigena S. Garaba et al. 10.5194/essd-15-4163-2023
- Monitoring of high biomass Phaeocystis globosa blooms in the Southern North Sea by in situ and future spaceborne hyperspectral radiometry H. Lavigne et al. 10.1016/j.rse.2022.113270
- An Evaluation of Sun-Glint Correction Methods for UAV-Derived Secchi Depth Estimations in Inland Water Bodies E. Tiškus et al. 10.3390/drones7090546
- Remote Sensing Retrieval of Water Clarity in Clear Oceanic to Extremely Turbid Coastal Waters From Multiple Spaceborne Sensors J. Xiang et al. 10.1109/TGRS.2023.3318590
- Evaluation of historic and new detection algorithms for different types of plastics over land and water from hyperspectral data and imagery A. Castagna et al. 10.1016/j.rse.2023.113834
- Towards global long-term water transparency products from the Landsat archive D. Maciel et al. 10.1016/j.rse.2023.113889
- Chromaticity-Based Discrimination of Algal Bloom from Inland and Coastal Waters Using In Situ Hyperspectral Remote Sensing Reflectance D. Zhao et al. 10.3390/w16162276
- Variability of light absorption coefficients by different size fractions of suspensions in the southern Baltic Sea J. Meler et al. 10.5194/bg-20-2525-2023
- Holistic optical water type classification for ocean, coastal, and inland waters S. Bi & M. Hieronymi 10.1002/lno.12606
- Evaluation of eight band SuperDove imagery for aquatic applications Q. Vanhellemont 10.1364/OE.483418
1 citations as recorded by crossref.
Latest update: 20 Nov 2024
Short summary
Here we describe a dataset of optical measurements paired with the concentration and composition of dissolved and particulate components of water systems in Belgium. Sampling was performed over eight lakes, a coastal lagoon, an estuary, and coastal waters, covering the period of 2017 to 2019. The data cover a broad range of conditions and can be useful for development and evaluation of hyperspectral methods in hydrology optics and remote sensing.
Here we describe a dataset of optical measurements paired with the concentration and composition...
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