Validation of water reflectance products using an automated hyperspectral system (HYPERNETS site) in the Río de la Plata (Argentina) in a multi-mission perspective

DOGLIOTTI, A. I.; PIEGARI, E.; RUBINSTEIN, L.; PERNA. P

Conferencia; HYPERNETS Science Conference; 2023

Validation of water reflectance using in situ data is essential to ensure the quality of oceancolor satellite-derived products useful for water quality monitoring, like turbidity andchlorophyll-a concentration. The optically complex and highly turbid waters of the Río de laPlata (Argentina) is an ideal scenario to test atmospheric correction algorithms performance.In contrast to the numerous and expensive field campaigns required to gather enoughradiometric measurements for satellite validation, the use of automated instruments hasproven to be the most effective way to provide validation data for earth observation systems.In particular, the hyperspectral radiometer HYPSTAR® (HYperspectral Pointable System for Terrestrial and Aquatic Radiometry) with a pointing system and auxiliary sensors, developed in the context of HYPERNETS H2020 project, provides water reflectance at fine spectral resolution (3nm FWHM) in the 350-1100nm region and with high temporal resolution (e.g. every 20 min) for radiometric validation of all visible and near-infrared bands of all existing and future optical missions, including nanosatellites. This system has been deployed at the end of a 1.1 km long jetty in the turbid waters of Río de la Plata, 60 km south of Buenos Aires (Argentina), in December 2021 and has been collecting data every 20 min from 9 am to 6 pm (local time). In the present study the site is characterized in relation to the spectral features and temporal patterns of water reflectance and compared to existing data in the estuary. Its spatial variability (homogeneity) is evaluated analyzing a time series of high spatial resolution S2/MSI turbidity maps at the site location. And finally in situ data collected autonomously have been compared with surface water reflectance data from many satellites, like Landsat-8/9, Sentinel-2 & Sentinel-3, MODIS-Aqua, VIIRS, PlanetScope CubeSats, and PRISMA. The best performing atmospheric correction algorithm for each system is presented. Results show the great potential of this automated system to provide high quality and quantity of data for validation of satellite data at all wavelengths in a multi-mission perspective.