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Evaluation of atmospheric correction algorithms for Sentinel-2-MSI and Sentinel-3-OLCI in highly turbid estuarine waters
Renosh, P.R.; Doxaran, D.; De Keukelaere, L.; Gossn, J.I. (2020). Evaluation of atmospheric correction algorithms for Sentinel-2-MSI and Sentinel-3-OLCI in highly turbid estuarine waters. Remote Sens. 12(8): 1285.
In: Remote Sensing. MDPI: Basel. ISSN 2072-4292; e-ISSN 2072-4292, more
Peer reviewed article  

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Author keywords
    ocean color remote sensing; atmospheric correction; Landsat-8-OLI; Sentinel-2-MSI; Sentinel-3-OLCI; highly turbid waters; suspended particulate matter

Authors  Top 
  • Renosh, P.R.
  • Doxaran, D.
  • De Keukelaere, L., more
  • Gossn, J.I.

    The present study assesses the performance of state-of-the-art atmospheric correction (AC) algorithms applied to Sentinel-2-MultiSpectral Instrument (S2-MSI) and Sentinel-3-Ocean and Land Color Instrument (S3-OLCI) data recorded over moderately to highly turbid estuarine waters, considering the Gironde Estuary (SW France) as a test site. Three spectral bands of water-leaving reflectance (Rhow) are considered: green (560 nm), red (655 or 665 nm) and near infrared (NIR) (865 nm), required to retrieve the suspended particulate matter (SPM) concentrations in clear to highly turbid waters (SPM ranging from 1 to 2000 mg/L). A previous study satisfactorily validated Acolite short wave infrared (SWIR) AC algorithm for Landsat-8-Operational Land Imager (L8-OLI) in turbid estuarine waters. The latest version of Acolite Dark Spectrum Fitting (DSF) is tested here and shows very good agreement with Acolite SWIR for OLI data. L8-OLI satellite data corrected for atmospheric effects using Acolite DSF are then used as a reference to assess the validity of atmospheric corrections applied to other satellite data recorded over the same test site with a minimum time difference. Acolite DSF and iCOR (image correction for atmospheric effects) are identified as the best performing AC algorithms among the tested AC algorithms (Acolite DSF, iCOR, Polymer and C2RCC (case 2 regional coast color)) for S2-MSI. Then, the validity of six different AC algorithms (OLCI Baseline Atmospheric Correction (BAC), iCOR, Polymer, Baseline residual (BLR), C2RCC-V1 and C2RCC-V2) applied to OLCI satellite data is assessed based on comparisons with OLI and/or MSI Acolite DSF products recorded on a same day with a minimum time lag. Results show that all the AC algorithms tend to underestimate Rhow in green, red and NIR bands except iCOR in green and red bands. The iCOR provides minimum differences in green (slope = 1.0 +/- 0.15, BIAS = 1.9 +/- 4.5% and mean absolute percentage error (MAPE) = 12 +/- 5%) and red (slope = 1.0 +/- 0.17, BIAS = -9.8 +/- 9% and MAPE = 28 +/- 20%) bands with Acolite DSF products from OLI and MSI data. For the NIR band, BAC provides minimum differences (slope = 0.7 +/- 0.13, BIAS = -33 +/- 17% and MAPE = 55 +/- 20%) with Acolite DSF products from OLI and MSI data. These results based on comparisons between almost simultaneous satellite products are supported by match-ups between satellite-derived and field-measured SPM concentrations provided by automated turbidity stations. Further validation of satellite products based on rigorous match-ups with in-situ Rhow measurements is still required in highly turbid waters.

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