An Optimal Strategy for Applying Combined Atmospheric Correction Approaches to Sentinel-2 MSI Over Inland and Coastal Waters

Reliable atmospheric correction (AC) is a prerequisite for quantitative water color remote sensing. However, the complex and variable optical properties of coastal and inland waters—particularly in regions with spatial intermixing of clear and turbid waters—present significant challenges to achieving stable and consistent results with existing AC algorithms. To solve this problem, this study introduces an atmospheric correction combination strategy for Sentinel-2 MSI, termed Atmospheric Correction Approach combining POLYMER and ACOLITE (ACA<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PO-AC</sub>) , which integrates the strengths of POLYMER in clear waters and ACOLITE-DSF in turbid waters. By constructing a logistic function based on the ratio of near-infrared to green bands, the strategy effectively captures the continuous transition between clear and turbid waters.The performance of ACA<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PO-AC</sub> was evaluated using a global in situ dataset. The results indicate that the ACA<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PO-AC</sub> achieves a coefficient of determination (R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>) exceeding 0.64 for all bands, with (R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>) exceeding 0.77 from 492 nm to 783 nm, and the mean relative percentage deviation (MAPD) for visible bands remaining below 50%. Compared to POLYMER and ACOLITE-DSF, the ACA<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PO-AC</sub> achieved slopes closest to 1 and the lowest bias and root mean square error (RMSE) across all bands (|bias|< 0.0015 sr<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup>,RMSE < 0.005 sr<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup>).Furthermore, the spatial pattern analyses of R<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub> and total suspended solids (TSS) confirm that this strategy enables smooth and consistent transitions between clear and turbid waters.

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Journal
IEEE Transactions on Geoscience and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/tgrs.2025.3583314
Primary Topic
Oceanographic and Atmospheric Processes
Type
article
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0.00

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article

An Optimal Strategy for Applying Combined Atmospheric Correction Approaches to Sentinel-2 MSI Over Inland and Coastal Waters

Liqiao Tian, Lan Zhang, Jilin Men, Xianghan Sun et al.
IEEE Transactions on Geoscience and Remote Sensing
Oceanographic and Atmospheric Processes
article

An Optimal Strategy for Applying Combined Atmospheric Correction Approaches to Sentinel-2 MSI Over Inland and Coastal Waters

Liqiao Tian, Lan Zhang, Jilin Men, Xianghan Sun, Xi Chen, Wenkai Li, Hongmei Zhao
article en

Abstract

Reliable atmospheric correction (AC) is a prerequisite for quantitative water color remote sensing. However, the complex and variable optical properties of coastal and inland waters—particularly in regions with spatial intermixing of clear and turbid waters—present significant challenges to achieving stable and consistent results with existing AC algorithms. To solve this problem, this study introduces an atmospheric correction combination strategy for Sentinel-2 MSI, termed Atmospheric Correction Approach combining POLYMER and ACOLITE (ACA<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PO-AC</sub>) , which integrates the strengths of POLYMER in clear waters and ACOLITE-DSF in turbid waters. By constructing a logistic function based on the ratio of near-infrared to green bands, the strategy effectively captures the continuous transition between clear and turbid waters.The performance of ACA<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PO-AC</sub> was evaluated using a global in situ dataset. The results indicate that the ACA<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PO-AC</sub> achieves a coefficient of determination (R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>) exceeding 0.64 for all bands, with (R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>) exceeding 0.77 from 492 nm to 783 nm, and the mean relative percentage deviation (MAPD) for visible bands remaining below 50%. Compared to POLYMER and ACOLITE-DSF, the ACA<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PO-AC</sub> achieved slopes closest to 1 and the lowest bias and root mean square error (RMSE) across all bands (|bias|< 0.0015 sr<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup>,RMSE < 0.005 sr<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup>).Furthermore, the spatial pattern analyses of R<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub> and total suspended solids (TSS) confirm that this strategy enables smooth and consistent transitions between clear and turbid waters.

IEEE Transactions on Geoscience and Remote SensingVol. 63
University of Alabama (US), Wuhan University (CN), Institute of Oceanology (CN), South China Sea Institute Of Oceanology (CN), State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN), Eastern Institute of Technology, Ningbo, Jiangxi Normal University (CN)
National Natural Science Foundation of China
Life below water
Openalex Percentile: Top 84%
Oceanographic and Atmospheric Processes
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