Validation of Sentinel-2/MSI Water Reflectance Using Automatic Hyperspectral In-Situ Observations in the Turbid Waters of Río de la Plata, Argentina (HYPERNETS Site)

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

Roma

Encuentro; Sentinel-2 Validation Team Meeting 2022; 2022

Validation of satellite-derived products, inparticular water reflectance, using insitu data is essential to ensure the quality of derived parameters, liketurbidity and chlorophyll-a concentration (Chl-a), useful for water quality monitoring. The use of autonomoussystems, like AERONET-OC, has shown to be effective for increasing the numberof validation match-ups compared to oceanographic cruises. However, the multispectralnature of the instrument used in the AERONET-OC network, prevents its use tovalidate missions with different spectral band configurations. In the frame ofH2020/HYPERNETS project, a new hyperspectral radiometer (HYPSTAR®) with a pointing system and auxiliary sensors havebeen designed to provide fine spectral resolution (2nm FWHM) in the VIS/NIRregion with high quality measurements at lower cost. Within this project an autonomoushyperspectral system has been deployed for the first time in the turbid watersof Río de la Plata estuary close to the city of Buenos Aires in South America, an ideal scenario to test atmospheric correction algorithms performance.In the present study, we assessed theperformance of different atmospheric correction, like DSF (Dark Spectral Fitting),CC2RR (Case 2 RegionalCoastColour), iCOR (imageCORrection for atmospheric effects), POLYMER (POLYnomial based algorithm applied to MERIS),and GRS (Glint Removal for Sentinel-2) processors applied to Sentinel-2 A/B data using one month of automaticin situ measurements collected incoincidence with the S2 satellite overpasses during that period.