Articles | Volume 15, issue 13
https://doi.org/10.5194/bg-15-4271-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-15-4271-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Phytoplankton size class in the East China Sea derived from MODIS satellite data
Hailong Zhang
School of Marine Sciences, Nanjing University of Information Science
& Technology, Nanjing, Jiangsu, China
Jiangsu Research Centre for Ocean Survey Technology, NUIST,
Nanjing, Jiangsu, China
Shengqiang Wang
School of Marine Sciences, Nanjing University of Information Science
& Technology, Nanjing, Jiangsu, China
Jiangsu Research Centre for Ocean Survey Technology, NUIST,
Nanjing, Jiangsu, China
Zhongfeng Qiu
CORRESPONDING AUTHOR
School of Marine Sciences, Nanjing University of Information Science
& Technology, Nanjing, Jiangsu, China
Jiangsu Research Centre for Ocean Survey Technology, NUIST,
Nanjing, Jiangsu, China
Deyong Sun
School of Marine Sciences, Nanjing University of Information Science
& Technology, Nanjing, Jiangsu, China
Jiangsu Research Centre for Ocean Survey Technology, NUIST,
Nanjing, Jiangsu, China
Joji Ishizaka
Institute for Space-Earth Environmental Research, Nagoya
University, Nagoya, Japan
Shaojie Sun
College of Marine Science, University of South Florida, St.
Petersburg, Florida, USA
Yijun He
School of Marine Sciences, Nanjing University of Information Science
& Technology, Nanjing, Jiangsu, China
Jiangsu Research Centre for Ocean Survey Technology, NUIST,
Nanjing, Jiangsu, China
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Cited
13 citations as recorded by crossref.
- Remotely assessing and monitoring coastal and inland water quality in China: Progress, challenges and outlook Y. Xiong et al. 10.1080/10643389.2019.1656511
- A simple and effective method for monitoring floating green macroalgae blooms: a case study in the Yellow Sea H. Zhang et al. 10.1364/OE.27.004528
- Retrieving Phytoplankton Size Class from the Absorption Coefficient and Chlorophyll A Concentration Based on Support Vector Machine L. Deng et al. 10.3390/rs11091054
- A hybrid algorithm for estimating total nitrogen from a large eutrophic plateau lake using Orbita hyperspectral (OHS) satellite imagery J. Li et al. 10.1016/j.jag.2024.103971
- Dynamics of euphotic zone depth in the Bohai Sea and Yellow Sea S. Wang et al. 10.1016/j.scitotenv.2020.142270
- Estimation of Phytoplankton Size Classes in the Littoral Sea of Korea Using a New Algorithm Based on Deep Learning J. Kang et al. 10.3390/jmse10101450
- Linking phytoplankton absorption to community composition in Chinese marginal seas D. Sun et al. 10.1016/j.pocean.2021.102517
- Key Environmental Drivers of Summer Phytoplankton Size Class Variability and Decadal Trends in the Northern East China Sea J. Park et al. 10.3390/rs17111954
- Variability of particulate backscattering ratio and its relations to particle intrinsic features in the Bohai Sea, Yellow Sea, and East China Sea D. Sun et al. 10.1364/OE.27.003074
- Estimation of phytoplankton taxonomic groups in the Arctic Ocean using phytoplankton absorption properties: implication for ocean-color remote sensing H. Zhang et al. 10.1364/OE.26.032280
- Turbidity Estimation from GOCI Satellite Data in the Turbid Estuaries of China’s Coast J. Feng et al. 10.3390/rs12223770
- Spatial and temporal variations of satellite-derived phytoplankton size classes using a three-component model bridged with temperature in Marginal Seas of the Western Pacific Ocean H. Liu et al. 10.1016/j.pocean.2021.102511
- Two-decadal estimation of sixteen phytoplankton pigments from satellite observations in coastal waters D. Sun et al. 10.1016/j.jag.2022.102715
13 citations as recorded by crossref.
- Remotely assessing and monitoring coastal and inland water quality in China: Progress, challenges and outlook Y. Xiong et al. 10.1080/10643389.2019.1656511
- A simple and effective method for monitoring floating green macroalgae blooms: a case study in the Yellow Sea H. Zhang et al. 10.1364/OE.27.004528
- Retrieving Phytoplankton Size Class from the Absorption Coefficient and Chlorophyll A Concentration Based on Support Vector Machine L. Deng et al. 10.3390/rs11091054
- A hybrid algorithm for estimating total nitrogen from a large eutrophic plateau lake using Orbita hyperspectral (OHS) satellite imagery J. Li et al. 10.1016/j.jag.2024.103971
- Dynamics of euphotic zone depth in the Bohai Sea and Yellow Sea S. Wang et al. 10.1016/j.scitotenv.2020.142270
- Estimation of Phytoplankton Size Classes in the Littoral Sea of Korea Using a New Algorithm Based on Deep Learning J. Kang et al. 10.3390/jmse10101450
- Linking phytoplankton absorption to community composition in Chinese marginal seas D. Sun et al. 10.1016/j.pocean.2021.102517
- Key Environmental Drivers of Summer Phytoplankton Size Class Variability and Decadal Trends in the Northern East China Sea J. Park et al. 10.3390/rs17111954
- Variability of particulate backscattering ratio and its relations to particle intrinsic features in the Bohai Sea, Yellow Sea, and East China Sea D. Sun et al. 10.1364/OE.27.003074
- Estimation of phytoplankton taxonomic groups in the Arctic Ocean using phytoplankton absorption properties: implication for ocean-color remote sensing H. Zhang et al. 10.1364/OE.26.032280
- Turbidity Estimation from GOCI Satellite Data in the Turbid Estuaries of China’s Coast J. Feng et al. 10.3390/rs12223770
- Spatial and temporal variations of satellite-derived phytoplankton size classes using a three-component model bridged with temperature in Marginal Seas of the Western Pacific Ocean H. Liu et al. 10.1016/j.pocean.2021.102511
- Two-decadal estimation of sixteen phytoplankton pigments from satellite observations in coastal waters D. Sun et al. 10.1016/j.jag.2022.102715
Discussed (final revised paper)
Latest update: 03 Jul 2025
Short summary
The PSC model was re-tuned for regional application in the East China Sea, and successfully applied to MODIS data. We investigated previously unknown temporal–spatial patterns of the PSC in the ECS and analyzed their responses to environmental factors. The results show the PSC varied across both spatial and temporal scales, and was probably affected by the water column stability, upwelling, and Kuroshio. In addition, human activity and riverine discharge may impact the PSC dynamics.
The PSC model was re-tuned for regional application in the East China Sea, and successfully...
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