{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:53:25Z","timestamp":1760241205305,"version":"build-2065373602"},"reference-count":54,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2019,12,25]],"date-time":"2019-12-25T00:00:00Z","timestamp":1577232000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004000","name":"Guangzhou Science and Technology Program key projects","doi-asserted-by":"publisher","award":["201707020031"],"award-info":[{"award-number":["201707020031"]}],"id":[{"id":"10.13039\/501100004000","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41276182"],"award-info":[{"award-number":["41276182"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Research and Development Projects","award":["2018YFC1406604"],"award-info":[{"award-number":["2018YFC1406604"]}]},{"name":"Project of State Key Laboratory of Tropical Oceanography","award":["LTOZZ1705"],"award-info":[{"award-number":["LTOZZ1705"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Geostationary Ocean Color Imager (GOCI) sensor, with high temporal and spatial resolution (eight images per day at an interval of 1 hour, 500 m), is the world\u2019s first geostationary ocean color satellite sensor. GOCI provides good data for ocean color remote sensing in the Western Pacific, among the most turbid waters in the world. However, GOCI has no shortwave infrared (SWIR) bands making atmospheric correction (AC) challenging in highly turbid coastal regions. In this paper, we have developed a new AC algorithm for GOCI in turbid coastal waters by using quasi-synchronous Visible Infrared Imaging Radiometer Suite (VIIRS) data. This new algorithm estimates and removes the aerosol scattering reflectance according to the contributing aerosol models and the aerosol optical thickness estimated by VIIRS\u2019s near-infrared (NIR) and SWIR bands. Comparisons with other AC algorithms showed that the new algorithm provides a simple, effective, AC approach for GOCI to obtain reasonable results in highly turbid coastal waters.<\/jats:p>","DOI":"10.3390\/rs12010089","type":"journal-article","created":{"date-parts":[[2019,12,25]],"date-time":"2019-12-25T11:07:48Z","timestamp":1577272068000},"page":"89","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Atmospheric Correction of GOCI Using Quasi-Synchronous VIIRS Data in Highly Turbid Coastal Waters"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3581-2450","authenticated-orcid":false,"given":"Jie","family":"Wu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China"},{"name":"Guangdong Key Laboratory of Ocean Remote Sensing, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Chuqun","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China"},{"name":"Guangdong Key Laboratory of Ocean Remote Sensing, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Sravanthi","family":"Nukapothula","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China"},{"name":"Guangdong Key Laboratory of Ocean Remote Sensing, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1016\/S0034-4257(98)00095-9","article-title":"A sensitivity study of the SeaWiFS atmospheric correction algorithm: Effects of spectral band variations","volume":"67","author":"Wang","year":"1999","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"5651","DOI":"10.1080\/01431160500168793","article-title":"A refinement for the Rayleigh radiance computation with variation of the atmospheric pressure","volume":"26","author":"Wang","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_3","first-page":"2414","article-title":"Rayleigh radiance computations for satellite remote sensing: Accounting for the effect of sensor spectral response function","volume":"24","author":"Wang","year":"2016","journal-title":"Opt. Express"},{"key":"ref_4","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_5","doi-asserted-by":"crossref","unstructured":"Emberton, S., Chittka, L., Cavallaro, A., and Wang, M.H. (2016). Sensor Capability and Atmospheric Correction in Ocean Colour Remote Sensing. Remote Sens., 8.","DOI":"10.3390\/rs8010001"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1007\/s12601-012-0024-4","article-title":"Overview of Geostationary Ocean Color Imager (GOCI) and GOCI Data Processing System (GDPS)","volume":"47","author":"Ryu","year":"2012","journal-title":"Ocean Sci. J."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Hu, Z.F., Pan, D.L., He, X.Q., 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_8","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/j.hal.2014.08.010","article-title":"Harmful algal bloom (HAB) in the East Sea identified by the Geostationary Ocean Color Imager (GOCI)","volume":"39","author":"Choi","year":"2014","journal-title":"Harmful Algae"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.ecss.2017.07.004","article-title":"Hourly changes in sea surface salinity in coastal waters recorded by Geostationary Ocean Color Imager","volume":"196","author":"Liu","year":"2017","journal-title":"Estuar Coast Shelf Sci."},{"key":"ref_10","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. Ocean., 117.","DOI":"10.1029\/2012JC008046"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.rse.2015.02.007","article-title":"Advantages of high quality SWIR bands for ocean colour processing: Examples from Landsat-8","volume":"161","author":"Vanhellemont","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1080\/2150704X.2014.898192","article-title":"A new approach for atmospheric correction of MODIS imagery in turbid coastal waters: A case study for the Pearl River Estuary","volume":"5","author":"He","year":"2014","journal-title":"Remote Sens. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Wang, M.H., and Shi, W. (2005). Estimation of ocean contribution at the MODIS near-infrared wavelengths along the east coast of the US: Two case studies. Geophys. Res. Lett., 32.","DOI":"10.1029\/2005GL022917"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"15722","DOI":"10.1364\/OE.15.015722","article-title":"The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing","volume":"15","author":"Wang","year":"2007","journal-title":"Opt. Express"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"21657","DOI":"10.1364\/OE.22.021657","article-title":"Improved near-infrared ocean reflectance correction algorithm for satellite ocean color data processing","volume":"22","author":"Jiang","year":"2014","journal-title":"Opt. Express"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1142","DOI":"10.1109\/TGRS.2013.2247768","article-title":"Early On-Orbit Performance of the Visible Infrared Imaging Radiometer Suite Onboard the Suomi National Polar-Orbiting Partnership (S-NPP) Satellite","volume":"52","author":"Cao","year":"2014","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Shi, W., Zhang, Y.L., and Wang, M.H. (2018). Deriving Total Suspended Matter Concentration from the Near-Infrared-Based Inherent Optical Properties over Turbid Waters: A Case Study in Lake Taihu. Remote Sens., 10.","DOI":"10.3390\/rs10020333"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"11664","DOI":"10.1002\/2013JD020418","article-title":"Suomi NPP VIIRS sensor data record verification, validation, and long-term performance monitoring","volume":"118","author":"Cao","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_19","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_20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2112\/SI74-001.1","article-title":"Hydrography-Physical Description of the Bohai Sea","volume":"74","author":"Bian","year":"2016","journal-title":"J. Coast. Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.csr.2014.03.006","article-title":"Seasonal distribution of suspended sediment in the Bohai Sea, China","volume":"90","author":"Wang","year":"2014","journal-title":"Cont. Shelf Res."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/0079-6611(86)90045-5","article-title":"Suspended Matter Regime in the Yellow Sea","volume":"17","author":"Milliman","year":"1986","journal-title":"Prog. Oceanogr."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Min, J.E., Choi, J.K., Yang, H., Lee, S., and Ryu, J.H. (2014). Monitoring changes in suspended sediment concentration on the southwestern coast of Korea. J. Coast. Res., 133\u2013138.","DOI":"10.2112\/SI70-023.1"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.ecss.2011.04.003","article-title":"Sediment transport in the Yellow Sea and East China Sea","volume":"93","author":"Dong","year":"2011","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.ecss.2015.03.008","article-title":"Seasonal variations of transport time of freshwater exchanges between Changjiang Estuary and its adjacent regions","volume":"157","author":"Wang","year":"2015","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/0278-4343(89)90085-X","article-title":"Changjiang River Plume and Suspended Sediment Transport in Hangzhou Bay","volume":"9","author":"Su","year":"1989","journal-title":"Cont. Shelf Res."},{"key":"ref_27","unstructured":"Saito, Y., and Yang, Z.S. (1995). Historical change of the Huanghe (Yellow River) and its impact on the sediment budget of the East China Sea. Global Fluxs of Carbon and Its Related Substances in the Coastal Sea-Ocean Atmosphere System, M & J International."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.jmarsys.2013.03.013","article-title":"Distributions of suspended sediment concentration in the Yellow Sea and the East China Sea based on field surveys during the four seasons of 2011","volume":"121","author":"Bian","year":"2013","journal-title":"J. Mar. Syst."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"5908","DOI":"10.1002\/2013JC009116","article-title":"An exploratory model study of sediment transport sources and deposits in the Bohai Sea, Yellow Sea, and East China Sea","volume":"118","author":"Bian","year":"2013","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1023\/A:1004953215589","article-title":"The visible solar spectral irradiance from 350 to 850 nm as measured by the SOLSPEC spectrometer during the ATLAS I mission","volume":"177","author":"Thuillier","year":"1998","journal-title":"Sol. Phys."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"7754","DOI":"10.1364\/AO.33.007754","article-title":"Influence of Oceanic Whitecaps on Atmospheric Correction of Ocean-Color Sensors","volume":"33","author":"Gordon","year":"1994","journal-title":"Appl. Opt."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"4790","DOI":"10.1364\/AO.40.004790","article-title":"Correction of sun glint contamination on the SeaWiFS ocean and atmosphere products","volume":"40","author":"Wang","year":"2001","journal-title":"Appl. Opt."},{"key":"ref_33","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_34","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_35","doi-asserted-by":"crossref","first-page":"173","DOI":"10.7780\/kjrs.2013.29.2.2","article-title":"Turbid water atmospheric correction for GOCI: Modification of MUMM algorithm","volume":"29","author":"Lee","year":"2013","journal-title":"Korean J. Remote Sens."},{"key":"ref_36","unstructured":"Park, Y.J., Ahn, Y.H., Han, H.J., Yang, H., Moon, J.E., Ahn, J.H., Lee, B.R., Min, J.E., Lee, S.J., and Kim, K.S. (2014). GOCI Level 2 Ocean Color Products (GDPS 1.3) Brief Algorithm Description, Korea Ocean Satellite Center, Korea Institute of Ocean Science and Technology."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1364\/AO.39.000897","article-title":"Atmospheric correction of SeaWiFS imagery for turbid coastal and inland waters","volume":"39","author":"Ruddick","year":"2000","journal-title":"Appl. Opt."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.rse.2012.12.006","article-title":"Evaluation of four atmospheric correction algorithms for MODIS-Aqua images over contrasted coastal waters","volume":"131","author":"Goyens","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(00)00080-8","article-title":"Atmospheric correction of SeaWiFS imagery over turbid coastal waters: A practical method","volume":"74","author":"Hu","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Huang, X.C., Zhu, J.H., Han, B., Jamet, C., Tian, Z., Zhao, Y.L., Li, J., and Li, T.J. (2019). Evaluation of Four Atmospheric Correction Algorithms for GOCI Images over the Yellow Sea. Remote Sens., 11.","DOI":"10.3390\/rs11141631"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"21176","DOI":"10.1364\/OE.21.021176","article-title":"Spectral relationships for atmospheric correction. II. Improving NASA\u2019s standard and MUMM near infra-red modeling schemes","volume":"21","author":"Goyens","year":"2013","journal-title":"Opt. Express"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"21162","DOI":"10.1364\/OE.21.021162","article-title":"Spectral relationships for atmospheric correction. I. Validation of red and near infra-red marine reflectance relationships","volume":"21","author":"Goyens","year":"2013","journal-title":"Opt. Express"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/S0034-4257(01)00341-8","article-title":"Spectral signature of highly turbid waters\u2014Application with SPOT data to quantify suspended particulate matter concentrations","volume":"81","author":"Doxaran","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1016\/j.rse.2008.11.005","article-title":"Evaluation of MODIS SWIR and NIR-SWIR atmospheric correction algorithms using SeaBASS data","volume":"113","author":"Wang","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3280","DOI":"10.1109\/TGRS.2012.2183376","article-title":"Sensor Noise Effects of the SWIR Bands on MODIS-Derived Ocean Color Products","volume":"50","author":"Wang","year":"2012","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Carswell, T., Costa, M., Young, E., Komick, N., Gower, J., and Sweeting, R. (2017). Evaluation of MODIS-Aqua Atmospheric Correction and Chlorophyll Products of Western North American Coastal Waters Based on 13 Years of Data. Remote Sens., 9.","DOI":"10.3390\/rs9101063"},{"key":"ref_47","first-page":"252","article-title":"Atmospheric Correction of Landsat-8\/OLI Imagery in Turbid Estuarine Waters: A Case Study for the Pearl River Estuary","volume":"10","author":"Ye","year":"2017","journal-title":"IEEE J. STARS"},{"key":"ref_48","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_49","doi-asserted-by":"crossref","first-page":"7887","DOI":"10.1364\/AO.36.007887","article-title":"Remote sensing of ocean color: Assessment of water-leaving radiance bidirectional effects on atmospheric diffuse transmittance","volume":"36","author":"Yang","year":"1997","journal-title":"Appl. Opt."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0169-8095(02)00174-6","article-title":"Spatial and temporal variability of aerosol: Size distribution and optical properties","volume":"66","author":"Masmoudi","year":"2003","journal-title":"Atmos. Res."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Queface, A.J., Piketh, S.J., Annegarn, H.J., Holben, B.N., and Uthui, R.J. (2003). Retrieval of aerosol optical thickness and size distribution from the CIMEL Sun photometer over Inhaca Island, Mozambique. J. Geophys. Res. Atmos., 108.","DOI":"10.1029\/2002JD002374"},{"key":"ref_52","unstructured":"Franz, B.A. (2016, January 08). rhoa_to_rhoas\u2014MS aerosol reflectance to SS aerosol reflectance, Aerosol.c in SeaDAS Code, Available online: http:\/\/seadas.gsfc.nasa.gov."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"3638","DOI":"10.3390\/rs4123638","article-title":"Impact of Aerosol Model Selection on Water-Leaving Radiance Retrievals from Satellite Ocean Color Imagery","volume":"4","author":"McCarthy","year":"2012","journal-title":"Remote Sens."},{"key":"ref_54","unstructured":"Cho, S. Introduction of GOCI and GOCI-II Mission with Lunar Calibration. Lunar Calibration Workshop, EUMETSAT. Available online: http:\/\/gsics.atmos.umd.edu\/pub\/Development\/ LunarCalibrationWorkshop\/4b_Cho_GOCI2.pdf."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/1\/89\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:45:44Z","timestamp":1760190344000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/1\/89"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,25]]},"references-count":54,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2020,1]]}},"alternative-id":["rs12010089"],"URL":"https:\/\/doi.org\/10.3390\/rs12010089","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2019,12,25]]}}}