Remote sensing of water turbidity in the Eastern China Seas from Geostationary Ocean Colour Imager

Abstract

ABSTRACTWater turbidity plays an important role in marine biogeochemical processes and ecosystem. Remote sensing of water turbidity in the Eastern China Seas is still a challenging task due to its large variations spanning more than three orders from coastal highly turbid waters to offshore clear waters. Thus, this study developed a new blended remote sensing algorithm for accurately estimating water turbidity in the whole Eastern China Seas from Geostationary Ocean Colour Imager (GOCI). The general idea of the new blended algorithm is to combine the band forms with the best abilities for deriving water turbidity in turbid waters and relatively clear waters, respectively. Evaluations based on field data showed a good performance of the new blended algorithm with values of the determination coefficient (R2), root-mean-square error (RMSE), mean absolute error (MAE), and mean relative error (MRE) of 0.884, 47.96 NTU, 29.59 and 48.13%, respectively. The proposed algorithm was applied to the GOCI data of 2015; and large spatiotemporal variations of water turbidity in the Eastern China Seas were observed. High values of water turbidity were observed in winter for both coastal and offshore waters, whereas the lowest values were observed in summer. Sediment resuspension drove by wind and tidal forcing, and sediment transportation related to current might be responsible for spatiotemporal variations of water turbidity, while the detailed study is required for further investigations. Overall, this study provides a technological basis which can be used to understand the variation patterns of water turbidity in the Eastern China Seas from GOCI satellite measurements.