Zeng, S; Lei, SH; Li, YM; Lyu, H; Xu, JF; Dong, XZ; Wang, R; Yang, ZQ; Li, JC (2020). Retrieval of Secchi Disk Depth in Turbid Lakes from GOCI Based on a New Semi-Analytical Algorithm. REMOTE SENSING, 12(9), 1516.

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(lambda)) data, a new semi-analytical algorithm (denoted as Z(SDZ)) for retrieving Z(SD) was developed from Rrs(lambda), 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 (R-2) 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.