Abstract

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 ( R h o w ) 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 R h o w 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 R h o w measurements is still required in highly turbid waters.

Highlights

  • Once corrected for atmospheric effects, ocean color satellite data can be used to retrieve and map suspended particulate matter (SPM) concentrations ranging from 1 to 2000 mg/L in coastal and estuarine waters [1]

  • Similar observations are made in the red band (665 nm) where Case 2 Regional Coast Color (C2RCC) and Polynomial based algorithm applied to MERIS (Polymer)-derived Rhow values are lower than expected based on results obtained with Acolite Dark Spectrum Fitting (DSF) and Image correction for atmospheric effects (iCOR), especially in the turbidity maximum zone (TMZ)

  • After regridding the images on a regular grid (300 m), pixel-by-pixel intercomparisons of the Rhow values were performed in the green, red and near infrared (NIR) spectral bands, the spectral bands required for the accurate retrieval of SPM concentrations within the wide range encountered in macro-tidal coastal waters and estuaries (1–2000 mg/L) [1,53,56]

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Summary

Introduction

Once corrected for atmospheric effects, ocean color satellite data can be used to retrieve and map suspended particulate matter (SPM) concentrations ranging from 1 to 2000 mg/L in coastal and estuarine waters [1]. Around 90% of the radiance received by satellite sensors results from the atmospheric contribution. In coastal waters, these contributions can be higher than 90% especially in the blue and green bands but are usually much lower in the red and near infrared (NIR) bands in the case of highly turbid waters associated with a higher reflectance signal [4]. LWN signal is computed by the following equation [8]: LWN(θv, φ) ≡

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