POSTER Session 1

Validating hyperspectral missions using the automated HYPERNETS system in the Río de la Plata highly turbid coastal waters

Validation of satellite-derived water reflectance using in situ data is an essential step in order to ensure the quality of ocean color products useful for water quality monitoring, like chlorophyll-a concentration. With the current hyperspectral missions, like EnMAP (Environmental Mapping and Analysis Program), PRISMA (PRecursore IperSpettrale della Missione Applicativa), DESIS (DLR Earth Sensing Imaging Spectrometer), and the recently launched PACE (Plankton, Aerosol, Cloud, Ocean Ecosystem), which are expected to provide more detailed information on phytoplankton composition, it is evident that hyperspectral in situ measurements for validation are essential. The HYPERNETS automated system, that uses the HYPSTAR (HYperspectral Pointable System for Terrestrial and Aquatic Radiometry) radiometer, collects data between 380-1020 nm with a FWHM of 3 nm on a routine basis, providing invaluable high quality and quantity of data for validation of such hyperspectral satellite systems. One of these HYPERNETS systems was deployed at the end of a 1.1 km long jetty in the Río de la Plata waters, 60 km south of Buenos Aires (Argentina), in December 2021 and has been collecting data every 20 min. The highly turbid waters of the Río de la Plata estuary represent a challenge and an ideal scenario to test atmospheric correction algorithm performance. In this study, we evaluated the performance of the standard and alternative ACOLITE atmospheric correction schemes applied to PRISMA, EnMAP and PACE hyperspectral images using simultaneous HYPSTAR data. In general the standard atmospheric correction for each mission tended to underestimate in situ measurements.

Ana Dogliotti, Instituto de Astronomía y Física del Espacio (IAFE), Argentina, https://orcid.org/0000-0001-8834-4374

Quinten Vanhellemont, Royal Belgian Institute of Natural Sciences (RBINS), Belgium

Kevin Ruddick, Royal Belgian Institute of Natural Sciences (RBINS), Belgium

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