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one publication added to basket [359394]

The HYPERMAQ dataset: bio-optical properties of moderately to extremely turbid waters Lavigne, H.; Dogliotti, A.; Doxaran, D.; Shen, F.; Castagna, A.; Beck, M.; Vanhellemont, Q.; Sun, X.; Gossn, J.I.; Renosh, P.R.; Sabbe, K.; Vansteenwegen, D.; Ruddick, K. (2022). The HYPERMAQ dataset: bio-optical properties of moderately to extremely turbid waters. ESSD 14(11): 4935-4947. https://dx.doi.org/10.5194/essd-14-4935-2022 In: Earth System Science Data. Copernicus: Göttingen. ISSN 1866-3508; e-ISSN 1866-3516

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Beschikbaar in	Auteurs
VLIZ: Open access 385052 [ download pdf ]

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Trefwoord

Marien/Kust

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Auteurs		Top
Lavigne, H. Dogliotti, A. Doxaran, D. Shen, F. Castagna, A.	Beck, M. Vanhellemont, Q. Sun, X. Gossn, J.I.	Renosh, P.R. Sabbe, K. Vansteenwegen, D. Ruddick, K.

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Abstract

Because of the large diversity of case 2 waters rangingfrom extremely absorbing to extremely scattering waters and the complexityof light transfer due to external terrestrial inputs, retrieving mainbiogeochemical parameters such as chlorophyll-a or suspended particulatematter concentration in these waters is still challenging. By providingoptical and biogeochemical parameters for 180 sampling stations withturbidity and chlorophyll-a concentration ranging from 1 to 700 FNU and from0.9 to 180 mg m−3 respectively, the HYPERMAQ dataset will contribute toa better description of marine optics in optically complex water bodies andcan help the scientific community to develop algorithms. The HYPERMAQ dataset provides biogeochemical parameters (i.e. turbidity, pigment and chlorophyll-a concentration, suspended particulate matter), apparent opticalproperties (i.e. water reflectance from above water measurements) and inherent optical properties (i.e. absorption and attenuation coefficients)from six different study areas. These study areas include large estuaries(i.e. the Rio de la Plata in Argentina, the Yangtze estuary in China, and the Gironde estuary in France), inland (i.e. the Spuikom in Belgium andChascomùs lake in Argentina), and coastal waters (Belgium). The dataset isavailable from Lavigne et al. (2022) at https://doi.org/10.1594/PANGAEA.944313.

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