{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T20:24:14Z","timestamp":1773692654093,"version":"3.50.1"},"reference-count":28,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T00:00:00Z","timestamp":1682035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41906025"],"award-info":[{"award-number":["41906025"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>High-frequency observations of surface current field data over large areas and long time series are imperative for comprehending sea-air interaction and ocean dynamics. Nonetheless, neither in situ observations nor polar-orbiting satellites can fulfill the requirements necessary for such observations. In recent years, geostationary satellite data with ultra-high temporal resolution have been increasingly utilized for the computation of surface flow fields. In this paper, the surface flow field in the East China Sea is estimated using maximum cross-correlation, which is the most widely used flow field computation algorithm, based on the total suspended solids (TSS) data acquired from the Geostationary Ocean Color Imager satellite. The inversion results were compared with the modeled tidal current data and the measured tidal elevation data for verification. The results of the verification demonstrated that the mean deviation of the long semiaxis of the tidal ellipse of the inverted M2 tide is 0.0335 m\/s, the mean deviation of the short semiaxis is 0.0276 m\/s, and the mean deviation of the tilt angle is 6.89\u00b0. Moreover, the spatially averaged flow velocity corresponds with the observed pattern of tidal elevation changes, thus showcasing the field\u2019s significant reliability. Afterward, we calculated the sea surface current fields in the East China Sea for the years 2013 to 2019 and created distribution maps for both climatology and seasonality. The resulting current charts provide an intuitive display of the spatial structure and seasonal variations in the East China Sea circulation. Lastly, we performed a diagnostic analysis on the surface TSS variation mechanism in the frontal zone along the Zhejiang coast, utilizing inverted flow data collected on 3 August 2013, which had a high spatial coverage and complete time series. Our analysis revealed that the intraday variation in TSS in the local surface layer was primarily influenced by tide-induced vertical mixing. The research findings of this article not only provide valuable data support for the study of local ocean dynamics but also verify the reliability of short-period surface flow inversion of high-turbidity waters near the coast using geostationary satellites.<\/jats:p>","DOI":"10.3390\/rs15082210","type":"journal-article","created":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T10:11:25Z","timestamp":1682071885000},"page":"2210","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["The Ocean Surface Current in the East China Sea Computed by the Geostationary Ocean Color Imager Satellite"],"prefix":"10.3390","volume":"15","author":[{"given":"Youzhi","family":"Ma","sequence":"first","affiliation":[{"name":"College of Marine Science and Technology, Zhejiang Ocean University, Zhoushan 316022, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8931-4975","authenticated-orcid":false,"given":"Wenbin","family":"Yin","sequence":"additional","affiliation":[{"name":"College of Marine Science and Technology, Zhejiang Ocean University, Zhoushan 316022, China"}]},{"given":"Zheng","family":"Guo","sequence":"additional","affiliation":[{"name":"College of Marine Science and Technology, Zhejiang Ocean University, Zhoushan 316022, China"}]},{"given":"Jiliang","family":"Xuan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"848","DOI":"10.1175\/1520-0485(1994)024<0848:CITBSB>2.0.CO;2","article-title":"Circulation in the Bering Sea basin observed by satellite-tracked drifters: 1986\u20131993","volume":"24","author":"Stabeno","year":"1994","journal-title":"J. Phys. Oceanogr."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1126\/science.198.4313.138","article-title":"Ocean Surface Currents Mapped by Radar: Mobile coastal units can map variable surface currents in real time to 70 kilometers, using ocean wave scatter","volume":"198","author":"Barrick","year":"1977","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Durand, F., Shankar, D., Birol, F., and Shenoi, S. (2009). Spatiotemporal structure of the East India Coastal Current from satellite altimetry. J. Geophys. Res. Oceans, 114.","DOI":"10.1029\/2008JC004807"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"12865","DOI":"10.1029\/JC091iC11p12865","article-title":"An objective method for computing advective surface velocities from sequential infrared satellite images","volume":"91","author":"Emery","year":"1986","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"852","DOI":"10.1175\/1520-0426(1990)007<0852:EOTMCC>2.0.CO;2","article-title":"Evaluation of the maximum cross-correlation method of estimating sea surface velocities from sequential satellite images","volume":"7","author":"Tokmakian","year":"1990","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1665","DOI":"10.1175\/1520-0426(2002)019<1665:EMSCFS>2.0.CO;2","article-title":"Extracting multiyear surface currents from sequential thermal imagery using the maximum cross-correlation technique","volume":"19","author":"Bowen","year":"2002","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1109\/TGRS.2006.883461","article-title":"Computing Coastal Ocean Surface Currents From Infrared and Ocean Color Satellite Imagery","volume":"45","author":"Crocker","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3988","DOI":"10.1002\/2014JC009981","article-title":"Application of the Geostationary Ocean Color Imager (GOCI) to estimates of ocean surface currents","volume":"119","author":"Yang","year":"2014","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1563","DOI":"10.1002\/2015JC011469","article-title":"Mapping surface tidal currents and Changjiang plume in the East China Sea from Geostationary Ocean Color Imager","volume":"121","author":"Hu","year":"2016","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Taniguchi, N., Kida, S., Sakuno, Y., Mutsuda, H., and Syamsudin, F. (2019). Short-Term Variation of the Surface Flow Pattern South of Lombok Strait Observed from the Himawari-8 Sea Surface Temperature. Remote Sens., 11.","DOI":"10.3390\/rs11121491"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1026","DOI":"10.1007\/s11430-019-9557-7","article-title":"Ocean surface current retrieval at Hangzhou Bay from Himawari-8 sequential satellite images","volume":"63","author":"Zhu","year":"2020","journal-title":"Sci. China Earth Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"9801","DOI":"10.1002\/2016GL070232","article-title":"Evolution of submesoscale coastal frontal waves in the East China Sea based on geostationary ocean color imager observational data","volume":"43","author":"Yin","year":"2016","journal-title":"Geophys. Res. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.jmarsys.2015.02.009","article-title":"Double SST fronts observed from MODIS data in the East China Sea off the Zhejiang\u2013Fujian coast, China","volume":"154","author":"He","year":"2016","journal-title":"J. Mar. Syst."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Choi, J.-K., Park, Y.J., Ahn, J.H., Lim, H.-S., Eom, J., and Ryu, J.-H. (2012). GOCI, the world\u2019s first geostationary ocean color observation satellite, for the monitoring of temporal variability in coastal water turbidity. J. Geophys. Res. Oceans, 117.","DOI":"10.1029\/2012JC008046"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"6533","DOI":"10.1002\/2017JC012830","article-title":"Episodic surface intrusions in the Yellow Sea during relaxation of northerly winds","volume":"122","author":"Hu","year":"2017","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.jmarsys.2015.04.005","article-title":"Tidal residual current and its role in the mean flow on the Changjiang Bank","volume":"154","author":"Xuan","year":"2016","journal-title":"J. Mar. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1002\/2014RG000450","article-title":"Accuracy assessment of global barotropic ocean tide models","volume":"52","author":"Stammer","year":"2014","journal-title":"Rev. Geophys."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"7113","DOI":"10.1109\/TGRS.2017.2741924","article-title":"Computing Ocean Surface Currents From GOCI Ocean Color Satellite Imagery","volume":"55","author":"Liu","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1677","DOI":"10.1175\/1520-0426(2002)019<1677:OCFSSI>2.0.CO;2","article-title":"Ocean currents from successive satellite images: The reciprocal filtering technique","volume":"19","author":"Barton","year":"2002","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Du, Y., Xu, Q., Cheng, Y., Zhang, S., and Wang, C. (2021, January 21\u201325). Estimating Sea Surface Currents Based on Himawari-8 Sea Surface Temperature Data. Proceedings of the 2021 Photonics & Electromagnetics Research Symposium (PIERS), Hangzhou, China.","DOI":"10.1109\/PIERS53385.2021.9695121"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1175\/1520-0485(1997)027<0403:STVOTK>2.0.CO;2","article-title":"Seasonal transport variations of the Kuroshio: An OGCM simulation","volume":"27","author":"Kagimoto","year":"1997","journal-title":"J. Phys. Oceanogr."},{"key":"ref_22","first-page":"1","article-title":"A sketch of the current structures and eddy characteristics in the East China Sea","volume":"27","author":"Guan","year":"1986","journal-title":"Stud. Mar. Sin."},{"key":"ref_23","unstructured":"Yu, H., Zheng, D., and Jiang, J. (1983, January 12\u201316). Basic hydrographic characteristics of the studied area. Proceedings of the International Symposium on Sedimentation on the Continental Shelf with Special Reference to the East China Sea, Hangzhou, China."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"6993","DOI":"10.1002\/2016JC011814","article-title":"Estimation of ocean surface currents from maximum cross correlation applied to GOCI geostationary satellite remote sensing data over the Tsushima (Korea) Straits","volume":"121","author":"Warren","year":"2016","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1381","DOI":"10.1007\/s11430-019-9618-7","article-title":"Tidal variation of total suspended solids over the Yangtze Bank based on the geostationary ocean color imager","volume":"63","author":"Zhou","year":"2020","journal-title":"Sci. China Earth Sci."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Hu, Z., Pan, D., He, X., and Bai, Y. (2016). Diurnal Variability of Turbidity Fronts Observed by Geostationary Satellite Ocean Color Remote Sensing. Remote Sens., 8.","DOI":"10.3390\/rs8020147"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1080\/01431161.2016.1268737","article-title":"Assessment of the MCC method to estimate sea surface currents in highly turbid coastal waters from GOCI","volume":"38","author":"Hu","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1038\/250404a0","article-title":"Fronts in the Irish sea","volume":"250","author":"Simpson","year":"1974","journal-title":"Nature"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/8\/2210\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:20:54Z","timestamp":1760124054000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/8\/2210"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,21]]},"references-count":28,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["rs15082210"],"URL":"https:\/\/doi.org\/10.3390\/rs15082210","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,21]]}}}