Evaluation of SDGSAT-1 MII data in total suspended matter estimation in clear to extremely turbid rivers

The Multispectral Imager (MII) onboard the newly launched SDGSAT-1 holds significant promise for monitoring and understanding variations in water quality within nearshore water systems, with an impressive spatial resolution of 10 m, seven spectral bands in the visible and near-infrared domain and a wide swath of 300 km. This paper evaluates the MII data in estimating the concentration of total suspended matter (TSM) in rivers and estuaries from clear to extremely turbid conditions. For atmospheric correction, the ACOLITE model showed superior performance compared to the FLAASH and 6SV, with average unbiased relative error (AURE) ranging from 11.8% to 26.4% in the four visible bands of MII. Through comparison, a TSM model based on the visible band ratio (i.e., Rrs(660)/Rrs(560)) was proposed to ensure the application of MII data in both clear and turbid waters, with an overall AURE of 40.9%. The model was then applied to map the TSM variations in the Hai and Liao Rivers in northern China using the MII data, where reliable spatial and temporal patterns were observed. The study concludes by discussing the applicability of MII data in water quality mapping in nearshore waters, along with key considerations such as model applicability, atmospheric correction, and land adjacency.

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Publication Details

Journal
International Journal of Digital Earth
Published
2024-11-05
DOI
https://doi.org/10.1080/17538947.2024.2413104
Citations
4
Primary Topic
Marine and coastal ecosystems
Type
article
Field-Weighted Citation Impact
1.92
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article

Evaluation of SDGSAT-1 MII data in total suspended matter estimation in clear to extremely turbid rivers

Changyong Dou, Fangfang Zhang, Bing Zhang, Xiaolong Yu et al.
4 citations
International Journal of Digital Earth
Marine and coastal ecosystems
1.92
article

Evaluation of SDGSAT-1 MII data in total suspended matter estimation in clear to extremely turbid rivers

Changyong Dou, Fangfang Zhang, Bing Zhang, Xiaolong Yu, Shenglei Wang, Fang Zhao, Junsheng Li, Xiaofei Song, Zichen Mao
article en
4 citations

Abstract

The Multispectral Imager (MII) onboard the newly launched SDGSAT-1 holds significant promise for monitoring and understanding variations in water quality within nearshore water systems, with an impressive spatial resolution of 10 m, seven spectral bands in the visible and near-infrared domain and a wide swath of 300 km. This paper evaluates the MII data in estimating the concentration of total suspended matter (TSM) in rivers and estuaries from clear to extremely turbid conditions. For atmospheric correction, the ACOLITE model showed superior performance compared to the FLAASH and 6SV, with average unbiased relative error (AURE) ranging from 11.8% to 26.4% in the four visible bands of MII. Through comparison, a TSM model based on the visible band ratio (i.e., Rrs(660)/Rrs(560)) was proposed to ensure the application of MII data in both clear and turbid waters, with an overall AURE of 40.9%. The model was then applied to map the TSM variations in the Hai and Liao Rivers in northern China using the MII data, where reliable spatial and temporal patterns were observed. The study concludes by discussing the applicability of MII data in water quality mapping in nearshore waters, along with key considerations such as model applicability, atmospheric correction, and land adjacency.

International Journal of Digital EarthVol. 17(1)
Xiamen University (CN), Chinese Academy of Sciences (CN), Ministry of Natural Resources (CN), China University of Mining and Technology (CN), China University of Geosciences (Beijing) (CN), Beijing Institute of Big Data Research (CN), Aerospace Information Research Institute (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 15%
Marine and coastal ecosystems
1.92
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