Mr. Rafael Merlo Profile

Rafael Merlo

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Proceedings Article | 17 October 2023 Presentation + Paper

Validation of Sentinel-2/MSI water reflectance and water quality products in the turbid waters of Río de la Plata estuary using fixed automated hyperspectral in situ observations

Ana Dogliotti, Rafael Merlo, Lilen Yema, Inés O'Farrell

Proceedings Volume 12728, 1272802 (2023) https://doi.org/10.1117/12.2684141

KEYWORDS: Turbidity, Water quality, Near infrared, Satellites, Atmospheric corrections, Radiometry, In situ metrology, Algorithm testing, Sensors

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Estimating water quality variables from satellite images requires an accurate estimation of the water reflectances (ρ_w) which mainly depends on the performance of the atmospheric correction applied. 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 December 2021 the hyperspectral radiometer HYPSTAR (HYperspectral Pointable System for Terrestrial and Aquatic Radiometry) with a pointing system and auxiliary sensors 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). This site is strategically located between a water intake and the active commercial harbour of La Plata city where intense phytoplankton blooms (including toxic Cyanobacteria) have been recorded frequently since 2020 presenting human health risks and causing temporal problems to the water intake site. The MultiSpectral Instrument (MSI) on board of Sentinel-2 mission provides high spatial resolution data which can be relevant for monitoring water quality parameters, like turbidity and chlorophyll-a concentration, around this site. In this study six month of automated hyperspectral in situ observations have been used to evaluate the standard Sen2Cor (SNAP) and the alternative DSF (ACOLITE) atmospheric correction algorithms for MSI. Furthermore, using in situ measurements collected during several field campaigns, a global turbidity algorithm and regionally tuned chlorophyll-a algorithms for S2/MSI bands have been evaluated and then applied to the S2/MSI time series showing its potential for water quality monitoring.

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