Improving remote sensing retrieval of global ocean transparency with optical water classification

Abstract

Ocean water transparency is an important indicator to measure the productivity of marine ecosystems, and it has great impact on phytoplankton biomass and community structure. Secchi disk depth (Zsd) is a traditional measure of water transparency. With the development of satellite remote sensing technology, inversion through empirical model or semi-analytical model has become an effective and efficient means to obtain ocean Zsd. In recent years, ocean parameter inversions based on water classification become an ongoing trend. Jia et al. (2021) constructed a fuzzy-logic optical water type scheme (i.e., U-OWT) for the global oceans and multi satellite sensors, which was a potential water classification template for remote sensing inversion of ocean Zsd. Using U-OWT as the water classification basis, and by collecting 613 global ocean distributed SeaWiFS (Sea-viewing Wide Field-of-view Sensor) Rrs and Zsd (with the range of 0.3–44.3 m) in-situ matchups, this study explored the optimal Zsd empirical models for each optical water type and each water trophic state respectively. As a result, a class-based Zsd hybrid empirical model (abbreviated as the Zsd-OWT model) was developed, which had relative high inversion accuracy over the entire Zsd range (MAPE = 8.25 %, RMSE = 0.65 m, bias = – 0.03 m). Specifically, the Zsd-OWT model conducted the global empirical inversion for the oligotrophic water classes and the class-based hard fusion empirical inversions for the mesotrophic and the eutrophic water classes. Although the Zsd-OWT model was designed for SeaWiFS sensor, it still has the potential to be migrated to other multispectral sensors with similar band settings.

Keywords

• Secchi disk depth
• Ocean color
• Optical water type
• SeaWiFS