Quantitative Retrieval of Chlorophyll-a Concentrations in the Bohai–Yellow Sea Using GOCI Surface Reflectance Products

• Published in: Remote sensing (Basel, Switzerland) Vol. 15; no. 22; p. 5285
• Main Authors: Wang, Jiru, Tang, Jiakui, Wang, Wuhua, Wang, Yanjiao, Wang, Zhao
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2023
• Subjects: Accuracy; Algorithms; Artificial intelligence; Artificial neural networks; Back propagation networks; Bohai–Yellow Sea; Brown, J.W; Carbon cycle (Biogeochemistry); Chlorophyll; chlorophyll-a concentration; Diurnal variations; Empirical analysis; Eutrophication; Geostationary Ocean Color Imager; GOCI surface reflectance products; Image processing; Inversion; Learning algorithms; Machine learning; Marine ecosystems; Monitoring; Neural networks; Ocean color; Reflectance; Remote sensing; remote sensing reflectance; Retrieval; Root-mean-square errors; Satellites; Sediments; Support vector machines; Temporal distribution; Water monitoring; Water quality; China; Yellow Sea; Bohai Sea

As an environmental parameter, the chlorophyll-a concentration (Chl-a) is essential for monitoring water quality and managing the marine ecosystem. However, current mainstream Chl-a inversion algorithms have limited accuracy and poor spatial and temporal generalization in Case II waters. In this stu...