A review of remote sensing of suspended sediment concentration in the Yellow River estuary

Xiaodong Bian; Dingfeng Yu; Shenliang Chen; Peng Li; Yanguo Fan; Chunyan Zhao

doi:10.1117/12.2622175

27 March 2022 A review of remote sensing of suspended sediment concentration in the Yellow River estuary

Xiaodong Bian, Dingfeng Yu, Shenliang Chen, Peng Li, Yanguo Fan, Chunyan Zhao

Proceedings Volume 12169, Eighth Symposium on Novel Photoelectronic Detection Technology and Applications; 1216916 (2022) https://doi.org/10.1117/12.2622175
Event: Eighth Symposium on Novel Photoelectronic Detection Technology and Applications, 2021, Kunming, China

Abstract

The Yellow River is one of the most sediment laden rivers in the world. It flows through the Loess Plateau and carries a large amount of sediment into the Bohai Sea. The sediment carried by the upper reaches of the Yellow River not only creates a large area of new land, but also affects the optical properties of the waters in the Yellow River Estuary.Suspended sediment content is one of the important parameters to characterize water quality. Many studies are devoted to the establishment of inversion models for quantitative inversion of suspended sediment concentration in the Yellow River Estuary. This paper summarizes the research progress of remote sensing retrieval of suspended sediment concentration in the Yellow River Estuary in recent years. The inversion algorithms for suspended sediment concentration in the Yellow River Estuary can be divided into three categories: empirical algorithm, semi analytical algorithm and analytical algorithm. The data sources for establishing the inversion model can be divided into measured spectral data and satellite data,in which the satellite data includes marine satellite data, Landsat data and meteorological satellite data. In view of the existing problems in the remote sensing inversion of suspended sediment concentration in the Yellow River Estuary, it is proposed that the future research should strengthen the spatiotemporal fusion of Multi-source Satellite data, develop the universal inversion model, and strengthen the application of machine learning algorithm and deep learning algorithm in this field

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Xiaodong Bian, Dingfeng Yu, Shenliang Chen, Peng Li, Yanguo Fan, and Chunyan Zhao "A review of remote sensing of suspended sediment concentration in the Yellow River estuary", Proc. SPIE 12169, Eighth Symposium on Novel Photoelectronic Detection Technology and Applications, 1216916 (27 March 2022); https://doi.org/10.1117/12.2622175

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KEYWORDS

Remote sensing

Satellites

Data modeling

Meteorological satellites

Reflectivity

Sensors

Water

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