POSTER Session 4

EVOLUTION OF THE SENTINEL-3 OLCI NEURAL NETWORK SWARM PROCESSING CHAIN FOR INLAND, COASTAL AND OCEAN WATERS

In the framework of the European Copernicus programme, global water surfaces are observed using the Ocean and Land Colour Instruments (OLCI) on board Sentinel-3 with a spatial resolution of approximately 300 m. This not only enables water quality monitoring of large-scale oceans, but also of optically more complex coastal and inland waters. The optical diversity of water bodies poses significant challenges for the processing algorithms, especially the atmospheric correction and the water algorithms. We provide an update on developments to the OLCI Neural Network Swarm (ONNS) algorithm, for which a novel atmospheric correction has been developed, its internal system for classifying optical water types has been improved and its biogeo-optical basis for deriving water constituents has been revised. A series of new satellite products are derived from this, e.g. on the carbon content in water bodies. A temporal sequence of daily aggregated observations provides unique insights into the dynamics of matter fluxes along the aquatic continuum of inland waters, coasts and oceans.

Martin Hieronymi, Helmholtz-Zentrum Hereon, Germany, [email protected], https://orcid.org/0000-0001-6066-1562

Shun Bi, Helmholtz-Zentrum Hereon, Germany, [email protected]

Daniel Behr, Helmholtz-Zentrum Hereon, Germany, [email protected]

Rüdiger Röttgers, Helmholtz-Zentrum Hereon, Germany, [email protected]

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