Multi-Scale Validation of Suspended Sediment Retrievals in Dynamic Estuaries: Integrating Geostationary and Low-Earth-Orbiting Optical Imagery for Hangzhou Bay

Water color remote sensing is vital for the monitoring and quantification of marine suspended sediment dynamics and their distributions. Yet validations of these observables in coastal regions and deltaic estuaries, including the Hangzhou Bay in the East China Sea, remain challenging, primarily due to the pronounced complex oceanic dynamics that exhibit high spatiotemporal variability in the signals of the suspended sediment concentration (SSC) in the ocean. Here, we integrate satellite images from the sun-synchronous satellites, China’s Huanjing (Chinese for environmental, HJ)-1A/B (charged couple device) CCD (30 m), and from Korea’s Geostationary Ocean Color Imager GOCI (500 m) to the spatiotemporal scale effects to validate SSC remote sensing-retrieved data products. A multi-scale validation framework based on coefficient of variation (CV)-based zoning was developed, where high-resolution HJ CCD SSC data were resampled to the GOCI scale (500 m), and spatial variability was quantified using CV values within corresponding HJ CCD windows. Traditional validation, comparing in situ point measurements directly with GOCI pixel-averaged data, introduces significant uncertainties due to pixel heterogeneity. The results indicate that in regions with high spatial heterogeneity (CV > 0.10), using central pixel values significantly weakens correlations and increases errors, with performance declining further in highly heterogeneous areas (CV > 0.15), underscoring the critical role of spatial averaging in mitigating scale-related biases. This study enhances the quantitative assessment of uncertainties in validating medium-to-low-resolution water color products, providing a robust approach for high-dynamic oceanic environment estuaries and bays.

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Publication Details

Journal
Remote Sensing
Published
2025-06-06
DOI
https://doi.org/10.3390/rs17121975
Primary Topic
Marine and coastal ecosystems
Type
article
Field-Weighted Citation Impact
0.00

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article

Multi-Scale Validation of Suspended Sediment Retrievals in Dynamic Estuaries: Integrating Geostationary and Low-Earth-Orbiting Optical Imagery for Hangzhou Bay

Jiangfei Wang, Bin Zhou, C. K. Shum, Xiaohong Yuan et al.
Remote Sensing
Marine and coastal ecosystems
article

Multi-Scale Validation of Suspended Sediment Retrievals in Dynamic Estuaries: Integrating Geostationary and Low-Earth-Orbiting Optical Imagery for Hangzhou Bay

Jiangfei Wang, Bin Zhou, C. K. Shum, Xiaohong Yuan, Wangbing Liu, Yiping Dai, Ben Wang, Zhifeng Yu
article en

Abstract

Water color remote sensing is vital for the monitoring and quantification of marine suspended sediment dynamics and their distributions. Yet validations of these observables in coastal regions and deltaic estuaries, including the Hangzhou Bay in the East China Sea, remain challenging, primarily due to the pronounced complex oceanic dynamics that exhibit high spatiotemporal variability in the signals of the suspended sediment concentration (SSC) in the ocean. Here, we integrate satellite images from the sun-synchronous satellites, China’s Huanjing (Chinese for environmental, HJ)-1A/B (charged couple device) CCD (30 m), and from Korea’s Geostationary Ocean Color Imager GOCI (500 m) to the spatiotemporal scale effects to validate SSC remote sensing-retrieved data products. A multi-scale validation framework based on coefficient of variation (CV)-based zoning was developed, where high-resolution HJ CCD SSC data were resampled to the GOCI scale (500 m), and spatial variability was quantified using CV values within corresponding HJ CCD windows. Traditional validation, comparing in situ point measurements directly with GOCI pixel-averaged data, introduces significant uncertainties due to pixel heterogeneity. The results indicate that in regions with high spatial heterogeneity (CV > 0.10), using central pixel values significantly weakens correlations and increases errors, with performance declining further in highly heterogeneous areas (CV > 0.15), underscoring the critical role of spatial averaging in mitigating scale-related biases. This study enhances the quantitative assessment of uncertainties in validating medium-to-low-resolution water color products, providing a robust approach for high-dynamic oceanic environment estuaries and bays.

Remote SensingVol. 17(12)
Hangzhou Normal University (CN), Zhejiang Environmental Monitoring Center (CN), The Ohio State University (US)
National Natural Science Foundation of China
Openalex Percentile: Top 86%
Marine and coastal ecosystems
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