The accurate remote estimation of the Secchi disk depth (Z_SD) in turbid waters is essential in the monitoring the ecological environment of lakes. Using the field measured Z_SD and the remote sensing reflectance (Rrs(λ)) data, a new semi-analytical algorithm (denoted as Z_SDZ) for retrieving Z_SD was developed from Rrs(λ), and it was applied to Geostationary Ocean Color Imager (GOCI) images in extremely turbid waters. Our results are as follows: (1) the Z_SDZ performs well in estimating Z_SD in turbid water bodies (0.15 m < Z_SD < 2.5 m). By validating with the field measured data that were collected in four turbid inland lakes, the determination coefficient (R²) is determined to be 0.89, with a mean absolute square percentage error (MAPE) of 22.39%, and root mean square error (RMSE) of 0.24 m. (2) The Z_SDZ improved the retrieval accuracy of Z_SD in turbid waters and outperformed the existing semi-analytical schemes. (3) The developed algorithm and GOCI data are in order to map the hourly variation of Z_SD in turbid inland waters, the GOCI-derived results reveal a significant spatiotemporal variation in our study region, which are significantly driven by wind forcing. This study can provide a new approach for estimating water transparency in turbid waters, offering important support for the management of inland waters.

Particle size distribution (PSD) is an important characterization parameter of the particle size structure of suspended particles, which is vulnerable to human activities such as sand dredging. In this study, sand dredging numbers were evaluated by the accumulated radiance algorithm using the night-time light composite data of the visible infrared imaging radiometer suite, and the PSD slope was derived by band ratio algorithm of Landsat-8/operational land imager (OLI) imagery. Then, the influence of sand mining on PSD slope was analyzed. We draw several crucial findings. First, the ratio of ${\bm{R}_{{{\bf rs}}({{{\bf Red}}})}}$ to ${\bm{R}_{{{\bf rs}}({{{\bf Green}}})}}$ based on OLI imagery was capable of retrieving PSD slope with good robustness (R2 = 0.71, p < 0.01, n = 41) and verified acceptance (mean absolute percentage error = 4.29%, root mean square error = 0.19, n = 20), and the PSD slope in HZL was lower in summer than in the other seasons from 2014 to 2017. Second, The night active vessels extracted from the night-time images show that sand dredging activities began at the outlet of Chengzi Lake (CZL) in April 2012, spread to the whole lake between 2014 and 2016, and then stopped in the northeast region in March 2017 due to the strict control of the local government. Third, the PSD slope is strongly influenced by sand mining, which is positively correlated with the number of sand dredgers (R2 = 0.92), i.e., the PSD slope increases 0.21 per 100 working sand dredgers in CZL.