{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T15:53:45Z","timestamp":1782402825505,"version":"3.54.5"},"reference-count":46,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,24]],"date-time":"2021-12-24T00:00:00Z","timestamp":1640304000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The first geostationary ocean color data from the Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) have been accumulating for more than ten years from 2010. This study performs a multi-year quality assessment of GOCI chlorophyll-a (Chl-a) and radiometric data for 2012\u20132021 with an advanced atmospheric correction technique and a regionally specialized Chl-a algorithm. We examine the consistency and stability of GOCI, Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) level 2 products in terms of annual and seasonal climatology, two-dimensional frequency distribution, and multi-year time series. Overall, the GOCI agrees well with MODIS and VIIRS on annual and seasonal variability in Chl-a, as the central biological pattern of the most transparent waters over the western North Pacific, productive waters over the East Sea, and turbid waters over the Yellow Sea are reasonably represented. Overall, an excellent agreement is remarkable for western North Pacific oligotrophic waters (with a correlation higher than 0.91 for Chl-a and 0.96 for band-ratio). However, the sporadic springtime overestimation of MODIS Chl-a values compared with others is notable over the Yellow Sea and East Sea due to the underestimation of MODIS blue-green band ratios for moderate-high aerosol optical depth. The persistent underestimation of VIIRS Chl-a values compared with GOCI and MODIS occurs due to inherent sensor calibration differences. In addition, the artificially increasing trends in GOCI Chl-a (+0.48 mg m\u22123 per 9 years) arise by the decreasing trends in the band ratios. However, decreasing Chl-a trends in MODIS and VIIRS (\u22120.09 and \u22120.08 mg m\u22123, respectively) are reasonable in response to increasing sea surface temperature. The results indicate GOCI sensor degradation in the late mission period. The long-term application of the GOCI data should be done with a caveat, however; planned adjustments to GOCI calibration (2022) in the following GOCI-II satellite will essentially eliminate the bias in Chl-a trends.<\/jats:p>","DOI":"10.3390\/rs14010072","type":"journal-article","created":{"date-parts":[[2021,12,27]],"date-time":"2021-12-27T01:06:54Z","timestamp":1640567214000},"page":"72","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Decadal Measurements of the First Geostationary Ocean Color Satellite (GOCI) Compared with MODIS and VIIRS Data"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1262-7786","authenticated-orcid":false,"given":"Myung-Sook","family":"Park","sequence":"first","affiliation":[{"name":"Korea Ocean Satellite Center (KOSC), Korea Institute of Ocean Science and Technology (KIOST), 385, Haeyang-ro, Yeongdo-gu, Busan 49111, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2176-1282","authenticated-orcid":false,"given":"Seonju","family":"Lee","sequence":"additional","affiliation":[{"name":"Korea Ocean Satellite Center (KOSC), Korea Institute of Ocean Science and Technology (KIOST), 385, Haeyang-ro, Yeongdo-gu, Busan 49111, Korea"},{"name":"Ocean Science, University of Science and Technology, Daejeon 34113, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2240-4562","authenticated-orcid":false,"given":"Jae-Hyun","family":"Ahn","sequence":"additional","affiliation":[{"name":"Korea Ocean Satellite Center (KOSC), Korea Institute of Ocean Science and Technology (KIOST), 385, Haeyang-ro, Yeongdo-gu, Busan 49111, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sun-Ju","family":"Lee","sequence":"additional","affiliation":[{"name":"Korea Ocean Satellite Center (KOSC), Korea Institute of Ocean Science and Technology (KIOST), 385, Haeyang-ro, Yeongdo-gu, Busan 49111, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9743-7636","authenticated-orcid":false,"given":"Jong-Kuk","family":"Choi","sequence":"additional","affiliation":[{"name":"Korea Ocean Satellite Center (KOSC), Korea Institute of Ocean Science and Technology (KIOST), 385, Haeyang-ro, Yeongdo-gu, Busan 49111, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joo-Hyung","family":"Ryu","sequence":"additional","affiliation":[{"name":"Korea Ocean Satellite Center (KOSC), Korea Institute of Ocean Science and Technology (KIOST), 385, Haeyang-ro, Yeongdo-gu, Busan 49111, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2594","DOI":"10.1126\/science.1055071","article-title":"Biospheric Primary Production During an ENSO Transition","volume":"291","author":"Behrenfeld","year":"2001","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1126\/science.281.5374.237","article-title":"Primary production of the biosphere: Integrating terrestrial and oceanic components","volume":"281","author":"Field","year":"1998","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"752","DOI":"10.1038\/nature05317","article-title":"Climate-driven trends in contemporary ocean productivity","volume":"444","author":"Behrenfeld","year":"2006","journal-title":"Nature"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1038\/s41467-019-08457-x","article-title":"Ocean colour signature of climate change","volume":"10","author":"Dutkiewicz","year":"2019","journal-title":"Nat. Commun."},{"key":"ref_5","unstructured":"Franz, B.A., Bailey, S.W., Meister, G., and Werdell, P.J. (2012, January 8\u201312). Quality and consistency of the NASA ocean color data record. Proceedings of the Ocean Optics XXI, Glasgow, UK."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"8702","DOI":"10.1364\/AO.51.008702","article-title":"On-orbit calibration of SeaWiFS","volume":"51","author":"Eplee","year":"2012","journal-title":"Appl. Opt."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"88661L","DOI":"10.1117\/12.2024069","article-title":"A Synthesis of VIIRS Solar and Lunar Calibrations","volume":"8866","author":"Eplee","year":"2013","journal-title":"Earth Obs. Syst. XVIII"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"5068","DOI":"10.1364\/AO.46.005068","article-title":"Sensor-independent approach to the vicarious calibration of satellite ocean color radiometry","volume":"46","author":"Franz","year":"2007","journal-title":"Appl. Opt."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1364\/AO.33.000443","article-title":"Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: A preliminary algorithm","volume":"33","author":"Gordon","year":"1994","journal-title":"Appl. Opt."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"275","DOI":"10.5194\/os-11-275-2015","article-title":"In situ autonomous optical radiometry measurements for satellite ocean color validation in the Western Black Sea","volume":"11","author":"Zibordi","year":"2015","journal-title":"Ocean Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/0034-4257(94)90073-6","article-title":"A simple, moderately accurate, atmospheric correction algorithm for SeaWiFS","volume":"50","author":"Wang","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.rse.2016.05.001","article-title":"VIIRS-derived chlorophyll-a using the ocean color index method","volume":"182","author":"Wang","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.dsr2.2003.06.003","article-title":"Satellite-measured seasonal and inter-annual chlorophyll variability in the Northeast Pacific and Coastal Gulf of Alaska","volume":"51","author":"Brickley","year":"2004","journal-title":"Deep Sea Res. Part II Top. Stud. Oceanogr."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/j.rse.2005.05.013","article-title":"Red tide detection and tracing using MODIS fluorescence data: A regional example in SW Florida coastal waters","volume":"97","author":"Hu","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2118","DOI":"10.1016\/j.rse.2009.05.012","article-title":"A novel ocean color index to detect floating algae in the global oceans","volume":"113","author":"Hu","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"6978","DOI":"10.1364\/AO.426137","article-title":"Seasonal bias in global ocean color observations","volume":"60","author":"Bisson","year":"2021","journal-title":"Appl. Opt."},{"key":"ref_17","first-page":"9004","article-title":"GOCI, the world\u2019s first geostationary ocean color observation satellite, for the monitoring of temporal variability in coastal water turbidity","volume":"117","author":"Hoi","year":"2012","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.hal.2018.02.006","article-title":"Remote quantification of Cochlodinium polykrikoides blooms occurring in the East Sea using geostationary ocean color imager (GOCI)","volume":"73","author":"Noh","year":"2018","journal-title":"Harmful Algae"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.rse.2013.06.020","article-title":"Retrieval of the seawater reflectance for suspended solids monitoring in the East China Sea using MODIS, MERIS and GOCI satellite data","volume":"146","author":"Doxaran","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1007\/s12601-012-0027-1","article-title":"Initial validation of GOCI water products against in situ data collected around Korean peninsula for 2010\u20132011","volume":"47","author":"Moon","year":"2012","journal-title":"Ocean Sci. J."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"29659","DOI":"10.1364\/OE.24.029659","article-title":"Simple aerosol correction technique based on the spectral relationships of the aerosol multiple-scattering reflectances for atmospheric correction over the oceans","volume":"24","author":"Ahn","year":"2016","journal-title":"Opt. Express"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1016\/j.rse.2016.07.031","article-title":"Evaluation of chlorophyll retrievals from Geostationary Ocean Color Imager (GOCI) for the North-East Asian region","volume":"184","author":"Kim","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"5545","DOI":"10.1364\/AO.49.005545","article-title":"New aerosol models for the retrieval of aerosol optical thickness and normalized water-leaving radiances from the SeaWiFS and MODIS sensors over coastal regions and open oceans","volume":"49","author":"Ahmad","year":"2010","journal-title":"Appl. Opt."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"5458","DOI":"10.1109\/TGRS.2015.2422831","article-title":"Correction of Stray-Light-Driven Interslot Radiometric Discrepancy (ISRD) Present in Radiometric Products of Geostationary Ocean Color Imager (GOCI)","volume":"53","author":"Kim","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1007\/s12601-012-0026-2","article-title":"Development of atmospheric correction algorithm for Geostationary Ocean Color Imager (GOCI)","volume":"47","author":"Ahn","year":"2012","journal-title":"Ocean Sci. J."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"23236","DOI":"10.1364\/OE.23.023236","article-title":"Vicarious calibration of the Geostationary Ocean Color Imager","volume":"23","author":"Ahn","year":"2015","journal-title":"Opt. Express"},{"key":"ref_27","unstructured":"Shettle, E.P., and Fenn, R.W. (1979). Models for the Aerosols of the Lower Atmosphere and the Effects of Humidity Variations on Their Optical Properties, Air Force Geophysics Laboratory, Air Force Systems Command, United States Air Force."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"7521","DOI":"10.1364\/OE.18.007521","article-title":"Estimation of near-infrared water-leaving reflectance for satellite ocean color data processing","volume":"18","author":"Bailey","year":"2010","journal-title":"Opt. Express"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"24937","DOI":"10.1029\/98JC02160","article-title":"Ocean color chlorophyll algorithms for SeaWiFS","volume":"103","author":"Maritorena","year":"1998","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1011","DOI":"10.1029\/2011JC007395","article-title":"Chlorophyll aalgorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference","volume":"117","author":"Hu","year":"2012","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_31","unstructured":"Antoine, D. (2004). Guide to the Creation and Use of Ocean-Colour, Level-3, Binned Data Products, International Ocean-Colour Coordinating Group (IOCCG). Reports of the International Ocean-Colour Coordinating Group, No. 4."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1023\/A:1011148910779","article-title":"Temporal and Spatial Variability of Phytoplankton Pigment Concentrations in the Japan Sea Derived from CZCS Images","volume":"56","author":"Kim","year":"2000","journal-title":"J. Oceanogr."},{"key":"ref_33","first-page":"169","article-title":"Bi-weekly to Seasonal Variability of Satellite-derived Chlorophyll a Distribution: Controlling Factors in the Ocean South of Honshu Island","volume":"25","author":"MIYASHITA","year":"2005","journal-title":"J. Remote Sens. Soc. Japan"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"45005","DOI":"10.1088\/1748-9326\/4\/4\/045005","article-title":"Estimation of chlorophyll-a concentration in case II waters using MODIS and MERIS data\u2014successes and challenges","volume":"4","author":"Moses","year":"2009","journal-title":"Environ. Res. Lett."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Wu, A., Mu, Q., Angal, A., and Xiong, X. (2020, January 21\u201325). Assessment of MODIS and VIIRS calibration consistency for reflective solar bands calibration using vicarious approaches. Proceedings of the Sensors, Systems, and Next-Generation Satellites XXIV, online.","DOI":"10.1117\/12.2573022"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"4619","DOI":"10.5194\/amt-12-4619-2019","article-title":"Validation, comparison, and integration of GOCI, AHI, MODIS, MISR, and VIIRS aerosol optical depth over East Asia during the 2016 KORUS-AQ campaign","volume":"12","author":"Choi","year":"2019","journal-title":"Atmos. Meas. Tech."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1016\/S0034-4257(02)00072-X","article-title":"Calibration of ocean color scanners: How much error is acceptable in the near infrared?","volume":"82","author":"Wang","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Park, M.-S., Choi, Y.-S., Ho, C.-H., Sui, C.-H., Park, S.K., and Ahn, M.-H. (2007). Regional cloud characteristics over the tropical northwestern Pacific as revealed by Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar and TRMM Microwave Imager. J. Geophys. Res. Atmos., 112.","DOI":"10.1029\/2006JD007437"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Ahn, J.-H., Park, Y.-J., and Fukushima, H. (2018). Comparison of Aerosol Reflectance Correction Schemes Using Two Near-Infrared Wavelengths for Ocean Color Data Processing. Remote Sens., 10.","DOI":"10.3390\/rs10111791"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"3139","DOI":"10.5194\/bg-7-3139-2010","article-title":"The most oligotrophic subtropical zones of the global ocean: Similarities and differences in terms of chlorophyll and yellow substance","volume":"7","author":"Morel","year":"2010","journal-title":"Biogeosciences"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"30191","DOI":"10.1364\/OE.27.030191","article-title":"Evaluating satellite estimates of particulate backscatter in the global open ocean using autonomous profiling floats","volume":"27","author":"Bisson","year":"2019","journal-title":"Opt. Express"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Wang, T., Chen, F., Zhang, S., Pan, J., Devlin, A.T., Ning, H., and Zeng, W. (2020). Remote Sensing and Argo Float Observations Reveal Physical Processes Initiating a Winter-Spring Phytoplankton Bloom South of the Kuroshio Current Near Shikoku. Remote Sens., 12.","DOI":"10.3390\/rs12244065"},{"key":"ref_43","first-page":"3143","article-title":"Bio-optical relationships and ocean color algorithms for the north polar region of the Atlantic","volume":"108","author":"Stramska","year":"2003","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.rse.2014.09.024","article-title":"Tracing floating green algae blooms in the Yellow Sea and the East China Sea using GOCI satellite data and Lagrangian transport simulations","volume":"156","author":"Son","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"111601","DOI":"10.1016\/j.rse.2019.111601","article-title":"Statistical evaluation of satellite ocean color data retrievals","volume":"237","author":"Mikelsons","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"74008","DOI":"10.1088\/1748-9326\/ab8527","article-title":"Two major modes of East Asian marine heatwaves","volume":"15","author":"Lee","year":"2020","journal-title":"Environ. Res. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/1\/72\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:53:01Z","timestamp":1760169181000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/1\/72"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,24]]},"references-count":46,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,1]]}},"alternative-id":["rs14010072"],"URL":"https:\/\/doi.org\/10.3390\/rs14010072","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,24]]}}}