Satellite Retrieval of Water Quality Indicators Under High Solar Zenith Angles

Accurate and high spatiotemporal resolution water quality data are critical for the effective management of marine and coastal ecosystems. However, accurate atmospheric correction under high solar zenith angles (SZA) remains a challenge, introducing substantial uncertainties in satellite-derived water quality indicators (WQI) under high SZA. With an attempt to fill the gap, this study evaluated three types of strategies for satellite retrieval of suspended particulate matter (SPM) and chlorophyll-a (Chl-a) concentrations from top-of-atmosphere reflectance (ρ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>t</i></sub>), Rayleigh-corrected reflectance (ρ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>rc</i></sub>) and remote sensing reflectance (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R<sub>rs</sub></i>), respectively. The models, named XGBWQI, based on three types of remote sensing data were tested with in-situ data and compared with the Geostationary Ocean Color Imager (GOCI) standard algorithms. Results showed that: (i) ρ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>t</i></sub>-based XGBWQI had the best accuracy (R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.90 and MAPD = 14.65% for SPM, R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.85 and MAPD = 5.34% for Chl-a); (ii) model testing results with in-situ data also confirmed the advantage of ρ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>t</i></sub>-based XGBWQI over other models (R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.88, MAPD = 26.9% and MRPD =11.8% for SPM, R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.78, MAPD = 43.3% and MRPD = -15.5% for Chl-a); and (iii) the XGBWQI models obtained more valid WQI values for GOCI images under high SZA and successfully revealed the diurnal variations of a red tide event in the Yellow Sea and the SPM dynamics in the East China Sea. Therefore, ρ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>t</i></sub>-based XGBWQI models were recommended as the best strategy for satellite retrievals of WQI under high SZA. The methods can serve as an effective tool in retrieving WQI in coastal waters under high SZA, and thus contribute to better and high-frequency water quality monitoring.

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Publication Details

Journal
IEEE Transactions on Geoscience and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/tgrs.2025.3580137
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Satellite Retrieval of Water Quality Indicators Under High Solar Zenith Angles

Huizeng Liu, Yu Zhang, Catherine C. L. Wong, Fang Shen et al.
IEEE Transactions on Geoscience and Remote Sensing
Water Quality Monitoring Technologies
article

Satellite Retrieval of Water Quality Indicators Under High Solar Zenith Angles

Huizeng Liu, Yu Zhang, Catherine C. L. Wong, Fang Shen, Yongquan Wang, Xiaolong Yu, Guofeng Wu, Qingquan Li, Zhengxin Zhang, Yanru Wang
article en

Abstract

Accurate and high spatiotemporal resolution water quality data are critical for the effective management of marine and coastal ecosystems. However, accurate atmospheric correction under high solar zenith angles (SZA) remains a challenge, introducing substantial uncertainties in satellite-derived water quality indicators (WQI) under high SZA. With an attempt to fill the gap, this study evaluated three types of strategies for satellite retrieval of suspended particulate matter (SPM) and chlorophyll-a (Chl-a) concentrations from top-of-atmosphere reflectance (ρ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>t</i></sub>), Rayleigh-corrected reflectance (ρ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>rc</i></sub>) and remote sensing reflectance (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R<sub>rs</sub></i>), respectively. The models, named XGBWQI, based on three types of remote sensing data were tested with in-situ data and compared with the Geostationary Ocean Color Imager (GOCI) standard algorithms. Results showed that: (i) ρ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>t</i></sub>-based XGBWQI had the best accuracy (R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.90 and MAPD = 14.65% for SPM, R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.85 and MAPD = 5.34% for Chl-a); (ii) model testing results with in-situ data also confirmed the advantage of ρ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>t</i></sub>-based XGBWQI over other models (R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.88, MAPD = 26.9% and MRPD =11.8% for SPM, R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.78, MAPD = 43.3% and MRPD = -15.5% for Chl-a); and (iii) the XGBWQI models obtained more valid WQI values for GOCI images under high SZA and successfully revealed the diurnal variations of a red tide event in the Yellow Sea and the SPM dynamics in the East China Sea. Therefore, ρ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>t</i></sub>-based XGBWQI models were recommended as the best strategy for satellite retrievals of WQI under high SZA. The methods can serve as an effective tool in retrieving WQI in coastal waters under high SZA, and thus contribute to better and high-frequency water quality monitoring.

IEEE Transactions on Geoscience and Remote SensingVol. 63
Stevens Institute of Technology (US), Shenzhen University (CN), Xiamen University (CN), East China Normal University (CN)
National Natural Science Foundation of China, Basic and Applied Basic Research Foundation of Guangdong Province
Clean water and sanitation
Openalex Percentile: Top 86%
Water Quality Monitoring Technologies
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