12:30–12:45 | ABSTRACT 1346
ADVANCES IN OCEAN COLOUR REMOTE SENSING WITHIN RENOMO – BRAZILIAN NATIONAL OCEAN OBSERVATION AND MONITORING NETWORK
The ReNOMO project, the Brazilian National Ocean Observation and Monitoring Network, was initiated in response to a demand from the Global Ocean Observing System (GOOS Brazil) to strengthen inter-institutional cooperation, focusing on practical actions to support ocean health. Within the ReNOMO structure, the remote sensing module aimed to validate and disseminate accurate satellite-derived biogeophysical products, such as chlorophyll-a, phytoplankton functional types, HABs, and particulate organic and inorganic matter. Through a collaborative framework, a unique dataset was assembled, including hyperspectral radiometry coupled with bio-optical, biogeophysical and hydrographic variables, addressing a major data gap in the South Atlantic. Algorithms applied to Sentinel-3 OLCI and Sentinel-2 MSI were evaluated using in situ data, significantly improving the retrieval and interpretation of surface chlorophyll-a, total suspended matter (TSM), and CDOM dynamics in optically complex coastal waters along the Brazilian coast. In addition, in situ and drone-based radiometry supported the evaluation of atmospheric correction algorithms. Proposed regional models successfully detected harmful algal blooms using Sentinel-2 and Sentinel-3 imagery, with dinoflagellate blooms identified in southern Brazil and the largest recorded bloom of Mesodinium rubrum mapped and analyzed off the coast of Rio de Janeiro. Hyperspectral models based on empirical orthogonal functions and generalized linear models provided accurate estimates of total chlorophyll-a and phytoplankton functional types (diatoms, dinoflagellates, haptophytes, and prasinophytes) in Brazilian coastal waters. Similarly, regional models based on in situ radiometry demonstrated robust performance in estimating organic and inorganic fractions of total suspended matter, supporting future applications with sensors such as PACE, EnMAP, and PRISMA.
Fernanda Giannini, Universidade Federal do Rio Grande, [email protected], https://orcid.org/0000-0002-8036-8483
Priscila Lange, INPO, [email protected]
Ana Paula Forgiarini, FURG, [email protected]
Aurea Ciotti, USP, [email protected]
Lino Sander, UFRJ, [email protected]
Vitor Cardoso, FURG, [email protected]
Wesley Santana, FURG, [email protected]
Catharina Cardoso, FURG, [email protected]
Nikolas Heinz, FURG, [email protected]
