POSTER SESSION 2
10:30–12:30, Tuesday, September 15
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ABSTRACT 1248 | POSTER 146
S2-LAG: A SENTINEL-2 PROCESSING CHAIN FOR OPERATIONAL MONITORING OF OPTICALLY COMPLEX COASTAL LAGOONS
Coastal lagoons are dynamic and vulnerable ecosystems whose monitoring under the Water Framework Directive (WFD) relies on key parameters such as chlorophyll-a concentration ([chl-a]) and water transparency (Zs). While in situ observations are essential, their limited spatial and temporal coverage hampers the characterization of coastal lagoon variability. Satellite remote sensing offers a complementary approach but remains challenged by atmospheric correction uncertainties, adjacency effects, bottom contamination, and high bio-optical complexity.
This study presents S2-LAG, a satellite processing chain designed for optically complex lagoon waters using Sentinel-2 MSI data, and evaluates its potential for operational monitoring. The approach combines an optimized atmospheric correction, a probabilistic algorithm to quantify bottom contamination, and locally calibrated inversion algorithms for key biogeochemical variables.
S2-LAG products are evaluated against in situ measurements and compared to standard Sentinel-3 OLCI products (OL_2_WFR_NN and OLCI-OC5). Results show that S2-LAG outperforms these products for the retrieval of [chl-a], suspended particulate matter ([SPM]) and Zs, with median relative errors of ~60%, ~37% and ~22%, respectively, while providing better spatial resolution (20 m).
Application to a 10-year Sentinel-2 time series (2015–2025) over the Berre and Thau lagoons (France) reveals key ecological dynamics with implications for management. Intense phytoplankton blooms occur predominantly outside WFD sampling periods, leading to an underestimation of eutrophication. Episodic ecological crises and changes in hydrological forcing are also identified, with impacts on water transparency and seagrass habitat suitability.
These results demonstrate that satellite products can provide robust and operational tools for ecological assessment and decision support in coastal lagoons.
Samuel Martin*, ACRI-ST, [email protected], https://orcid.org/0009-0009-6416-0373
David Doxaran, CNRS, [email protected], https://orcid.org/0000-0002-9778-7780
Philippe Bryère, ACRI-ST, [email protected]
Pierre Gernez, Nantes Université, [email protected], https://orcid.org/0000-0003-2055-410X
Antoine Mangin, ACRI-ST, [email protected]
Marine Bretagnon, ACRI-ST, [email protected], https://orcid.org/0000-0002-4429-6961
Poster Session | 1 | 2 | 3 | 4 | Schedule at a Glance
