The distribution of the surface suspended sand concentration (SSSC) in the Yangtze River estuary is extremely complex. Therefore, effective methods are needed to improve the efficiency and accuracy of SSSC inversion. Hyperspectral remote sensing technology provides an effective technical means of accurately monitoring and quantitatively inverting SSSC. In this study, a new framework for the accurate inversion of the SSSC in the Yangtze River estuary using hyperspectral remote sensing is proposed. First, we quantitatively simulated water bodies with different SSSCs using sediment samples from the Yangtze River estuary, and analyzed the spectral characteristics of water bodies with different SSSCs. On this basis, we compared six spectral transformation forms, and selected the first derivative (FD) transformation as the optimal spectral transformation form. Subsequently, we compared two feature band extraction methods: the successive projections algorithm (SPA) and the competitive adaptive reweighted sampling (CARS) method. Then, the partial least squares regression (PLSR) model and back propagation (BP) neural network model were constructed. The BP neural network model was determined as the best inversion model. The new FD-CARS-BP framework was applied to the airborne hyperspectral data of the Yangtze estuary, with R² of 0.9203, RPD of 4.5697, RMSE of 0.0339 kg/m³, and RMSE% of 8.55%, which are markedly higher than those of other framework combination forms, further verifying the effectiveness of the FD-CARS-BP framework in the quantitative inversion process of SSSC in the Yangtze estuary.

Introduction: The study on the distribution characteristics of suspended sediment concentration (SSC) in estuaries is an important subject in the study of estuaries and coasts, which has important theoretical significance and practical value.Methods: In order to fully understand the characteristics of SSC in the Yangtze River Estuary and its adjacent waters, this paper uses fixed vertical observation data and navigation type large area observation data as data sources to analyze the distribution characteristics of SSC in the Yangtze River Estuary and its adjacent waters under different tidal current states and its vertical profile characteristics. It discusses the impact of tidal current velocity on SSC and the changes of SSC in the Yangtze River Estuary and its adjacent waters from 2018 to 2020. And the applicability of the Rouse and Soulsby formulas in the Yangtze River Estuary and its adjacent waters was verified.Results: It was found that the Rouse and Soulsby models have high applicability in the study area, and the prediction accuracy based on the Li’s Soulsby model is higher. This study provides effective support for carrying out marine forecasting, analysis and evaluation, and provides theoretical basis for carrying out analysis of the current situation of estuarine mudflat resources and prediction of the evolution trend. It plays an important role in scientific and comprehensive research and management of mudflat resources in Shanghai.Discussion: However, this study only explored the characteristic patterns of SSC in the Yangtze River Estuary and its adjacent waters based on field observations, but SSC is a more complex water environment parameter that is influenced by a variety of factors. The effects of salinity, temperature and wind speed should be considered in subsequent studies.