The HYPERMAQ dataset

The HYPERMAQ dataset contributes to a better description of marine optics in optically complex water bodies by providing optical and biogeochemical parameters for 180 sampling stations with turbidity and chlorophyll-a concentration ranging between 1 to 700 FNU and between 0.9 to 180 mg m-3 respectively. The HYPERMAQ dataset is composed of biogeochemical parameters (i.e. turbidity, suspended particulate matter, chlorophyll-a and other phytoplankton pigments concentrations), apparent optical properties (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 waters (i.e. the Spuikom in Belgium and Chascomus Lake in Argentina) and coastal waters (Belgium). All data were collected between April and September 2018.

Data and Resources

This dataset has no data

Cite this as

Lavigne, Héloïse, Dogliotti, Ana I, Doxaran, David, Shen, Fang, Castagna, Alexandre, Beck, Matthew, Vanhellemont, Quinten, Sun, Xuerong, Gossn, Juan Ignacio, Renosh, Pannimpullath R, Sabbe, Koen, Vansteenwegen, Dieter, Ruddick, Kevin (2022). Dataset: The HYPERMAQ dataset. https://doi.org/10.1594/PANGAEA.944313

DOI retrieved: 2022

Additional Info

Field Value
Imported on November 30, 2024
Last update November 30, 2024
License CC-BY-4.0
Source https://doi.org/10.1594/PANGAEA.944313
Author Lavigne, Héloïse
Given Name Héloïse
Family Name Lavigne
More Authors
Dogliotti, Ana I
Doxaran, David
Shen, Fang
Castagna, Alexandre
Beck, Matthew
Vanhellemont, Quinten
Sun, Xuerong
Gossn, Juan Ignacio
Renosh, Pannimpullath R
Sabbe, Koen
Vansteenwegen, Dieter
Ruddick, Kevin
Source Creation 2022
Publication Year 2022
Resource Type application/zip - filename: Lavigne-etal_2022
Subject Areas
Name: Lithosphere

Related Identifiers
Title: The HYPERMAQ dataset: bio-optical properties of moderately to extremely turbid waters
Identifier: https://doi.org/10.5194/essd-14-4935-2022
Type: DOI
Relation: References
Year: 2022
Source: Earth System Science Data
Authors: Lavigne Héloïse , Dogliotti Ana I , Doxaran David , Shen Fang , Castagna Alexandre , Beck Matthew , Vanhellemont Quinten , Sun Xuerong , Gossn Juan Ignacio , Renosh Pannimpullath R , Sabbe Koen , Vansteenwegen Dieter , Ruddick Kevin .