Conference Agenda

In situ bio-optical datasets are essential for the assessment of the uncertainties of satellite ocean colour measurements and derived products. This is especially critical in coastal waters, where land adjacency effects, complex atmospheric aerosol mixtures, high loads of optically active components in particular high concentration of chromophoric dissolved organic matter and bottom reflectance effects contaminate the signal that reaches the satellite.

The Tara Europa expedition, the ocean component of the Traversing European Coastlines (TREC) program carried a comprehensive sampling of coastal ecosystems all along the European coast in 2023 and 2024. The Tara Europa expedition offered the unique opportunity of an oceanographic survey from a unique platform, using the same set of protocols, instruments, and sample analysis, collocated with a rich biological dataset describing the microbiologic diversity in detail.

Within the ESA-funded Hyperspectral Bio-Optical Observations Sailing on Tara (HyperBOOST) project, PML, CNR, LOV and UMaine extended the variables collected during the TREC integrated sampling by including bio-optical measurements relevant to present and future satellite ocean colour missions. This provided a comprehensive dataset encompassing in-situ hyperspectral radiometry, bio-optical properties, optically active components, biogeochemical and biodiversity relevant data for optically complex waters. Continuous inline optical measurements were combined with laboratory analyses of surface water samples collected at more than 200 stations along the European coasts.

This dataset will provide the opportunity to explore the complexity of Dissolved and Particulate Organic matter optical properties across the land-sea interface, opening the possibility to improve DOC and POC quantification from satellite imagery.

The diffuse export and biogeochemical processing of dissolved organic carbon (DOC) along coastlines remain under-quantified controls on coastal water quality and the ocean carbon cycle. Coastal DOC processes are difficult to quantify, because the coastal zone features steep gradients in DOC concentration and organic matter composition, dynamic biogeochemical and physical processes, and complex waters containing diverse sources in-water constituents. Hyperspectral imagery can facilitate the quantification of coastal DOC dynamics at large scales by separating multiple in-water constituents and characterizing subtle changes in ocean color to map biogeochemical and physical properties. To fully utilize a new generation of existing and planned hyperspectral satellite imagers, new regionally transferable algorithms are needed to retrieve coastal DOC concentration and composition at continental to global scales. To address this need, we developed hyperspectral algorithms for retrieving both DOC concentration as well as the quality and composition of colored dissolved organic matter (CDOM) in coastal waters characterized by varying water quality and ecological conditions. An in-situ dataset of hyperspectral radiometry, CDOM, DOC, and ancillary parameters was compiled from research cruises on the Atlantic, Gulf, Pacific, and Arctic coasts of the United States for algorithm development and validation. Algorithms utilizing hyperspectral ocean color, overall, outperformed existing multispectral approaches for retrieving coastal DOC and allowed for the retrieval of novel indicators of organic matter source and composition based on CDOM spectral shape. These algorithms were applied to hyperspectral satellite imagery of contrasting urbanized and natural coastal estuaries to demonstrate their utility and transferability for quantifying coastal DOC processes under diverse environmental conditions and anthropogenic impacts.

This study explores oceanic carbon fluxes from space by focusing on Net Community Production (NCP), the balance between primary production and community respiration. NCP estimates the if a region is consuming or producing carbon, which on long time scales can be translated to an estimate of carbon export flux. The project's goal is to develop a novel algorithm that estimates NCP directly from hyperspectral Rrs, without requiring ancillary data and capable of capturing both positive and negative NCP values in optically complex waters. To build the algorithm we are collecting in situ NCP and Rrs data in the South Atlantic Bight (SAB) region, which offers broad coastal-to-offshore gradients in both NCP and optical properties. NCP is measured using the Pressure of In Situ Gases Instrument (PIGI) flow-through system, which estimates NCP from dissolved oxygen and nitrogen gas concentrations, offering continuous measurements and a cost-effective alternative to traditional Oxygen/Argon methods. Concurrent hyperspectral remote sensing reflectance (Rrs) data is collected using the Solar Tracking Radiometry Platform (So-Rad), which provides high-resolution radiometric observations. Both instruments operate autonomously aboard the R/V Savannah, which primarily operates in the SAB. Here, we present initial results from the first field season (100 days in 2025), including early progress on neural network-based model development. Looking ahead, a second algorithm based on MODIS bands is planned to assess long-term trends in SAB NCP over the past 25 years using satellite data archives.