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      Dynamic Diurnal Changes in Green Algae Biomass in the Southern Yellow Sea Based on GOCI Images

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          Macroalgae blooms of Ulva prolifera have occurred every summer in the southern Yellow Sea since 2007, inducing severe ecological problems and huge economic losses. Genesis and secular movement of green algae blooms have been well monitored by using remote sensing and other methods. In this study, green algae were detected and traced by using Geostationary Ocean Color Imager (GOCI), and a novel biomass estimation model was developed from the relationship between biomass measurements and previously published satellite-derived biomass indexes. The results show that the green algae biomass can be determined most accurately with the biomass index of green algae for GOCI (BIGAG), which is calculated from the Rsurf data that had been atmospherically corrected by ENVI/QUAC method. For the first time, dynamic changes in green algae biomass were studied over an hourly scale. Short-term biomass changes were highly influenced by Photosynthetically Available Radiation (PAR) and tidal phases, but less by sea surface temperature variations on a daily timescale. A new parameter of biomass changes (PBC), calculated by the ratio of the biomass growth rate to movement velocity, could provide an effective way to assess and forecast green tide in the southern Yellow Sea and similar areas.

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          Author and article information

          Journal of Ocean University of China
          Science Press and Springer (China )
          10 July 2020
          01 August 2020
          : 19
          : 4
          : 811-817
          1State Key Laboratory of Marine Geology, Tongji University, Shanghai 200092, China
          2School of Civil Engineering and Geosciences, Newcastle University, Newcastle Upon Tyne NE3 1QD, UK
          3Institute of Oceanography, Zhejiang Geological Institute of China Metallurgical Geology Bureau, Quzhou 324000, China
          Author notes
          *Corresponding author: FAN Daidu, E-mail: ddfan@
          Copyright © Ocean University of China, Science Press and Springer-Verlag GmbH Germany 2020.

          The copyright to this article, including any graphic elements therein (e.g. illustrations, charts, moving images), is hereby assigned for good and valuable consideration to the editorial office of Journal of Ocean University of China, Science Press and Springer effective if and when the article is accepted for publication and to the extent assignable if assignability is restricted for by applicable law or regulations (e.g. for U.S. government or crown employees).

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