Validation of ocean color remote sensing reflectance data: Analysis of results at European coastal sites

• Published in: Remote Sensing of Environment
• Main Author: MELIN Frederic
• Language: English
• Published: ELSEVIER SCIENCE INC 2022
• Subjects: Aerosol Robotic Network
• Online Access: https://publications.jrc.ec.europa.eu/repository/handle/JRC129232; https://www.sciencedirect.com/science/article/pii/S003442572200267X; https://doi.org/10.1016/j.rse.2022.113153

From its initial measurements 20 years ago, the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) has produced large validation data sets to assess the ocean color satellite data records. This study, applied to the atmospheric correction algorithm l2gen of the National Aeronautics and Space Administration, analyses the populations of residuals (differences between satellite and field data) of remote sensing reflectance RRS and, secondarily, aerosol optical thickness τa, and their validation statistics associated with data collected at seven AERONET-OC sites in European coastal regions for six satellite missions. Validation statistics have been analyzed as a function of observation conditions, sites and missions. Uncertainty estimates for RRS appear to vary less across missions than across sites. For a given mission, RRS residuals are well correlated between bands, which has implications on the propagation of uncertainties through bio-optical algorithms. For a given wavelength, residuals are correlated between missions to various degrees. Besides implications as far as uncertainties of multi-mission merged products are concerned, this inter-mission correlation among residuals suggest that the residuals are not random and could be reduced. JRC.D.2 - Water and Marine Resources