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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics


  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 8, Iss. 3 — Apr. 4, 2013

Ocean color products from the Korean Geostationary Ocean Color Imager (GOCI)

Menghua Wang, Jae-Hyun Ahn, Lide Jiang, Wei Shi, SeungHyun Son, Young-Je Park, and Joo-Hyung Ryu  »View Author Affiliations

Optics Express, Vol. 21, Issue 3, pp. 3835-3849 (2013)

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The first geostationary ocean color satellite sensor, Geostationary Ocean Color Imager (GOCI), which is onboard South Korean Communication, Ocean, and Meteorological Satellite (COMS), was successfully launched in June of 2010. GOCI has a local area coverage of the western Pacific region centered at around 36°N and 130°E and covers ~2500 × 2500 km2. GOCI has eight spectral bands from 412 to 865 nm with an hourly measurement during daytime from 9:00 to 16:00 local time, i.e., eight images per day. In a collaboration between NOAA Center for Satellite Applications and Research (STAR) and Korea Institute of Ocean Science and Technology (KIOST), we have been working on deriving and improving GOCI ocean color products, e.g., normalized water-leaving radiance spectra (nLw(λ)), chlorophyll-a concentration, diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)), etc. The GOCI-covered ocean region includes one of the world’s most turbid and optically complex waters. To improve the GOCI-derived nLw(λ) spectra, a new atmospheric correction algorithm was developed and implemented in the GOCI ocean color data processing. The new algorithm was developed specifically for GOCI-like ocean color data processing for this highly turbid western Pacific region. In this paper, we show GOCI ocean color results from our collaboration effort. From in situ validation analyses, ocean color products derived from the new GOCI ocean color data processing have been significantly improved. Generally, the new GOCI ocean color products have a comparable data quality as those from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellite Aqua. We show that GOCI-derived ocean color data can provide an effective tool to monitor ocean phenomenon in the region such as tide-induced re-suspension of sediments, diurnal variation of ocean optical and biogeochemical properties, and horizontal advection of river discharge. In particular, we show some examples of ocean diurnal variations in the region, which can be provided effectively from satellite geostationary measurements.

© 2013 OSA

OCIS Codes
(010.0010) Atmospheric and oceanic optics : Atmospheric and oceanic optics
(010.1290) Atmospheric and oceanic optics : Atmospheric optics
(010.4450) Atmospheric and oceanic optics : Oceanic optics
(010.1285) Atmospheric and oceanic optics : Atmospheric correction

ToC Category:
Atmospheric and Oceanic Optics

Original Manuscript: January 23, 2013
Manuscript Accepted: January 27, 2013
Published: February 7, 2013

Virtual Issues
Vol. 8, Iss. 3 Virtual Journal for Biomedical Optics

Menghua Wang, Jae-Hyun Ahn, Lide Jiang, Wei Shi, SeungHyun Son, Young-Je Park, and Joo-Hyung Ryu, "Ocean color products from the Korean Geostationary Ocean Color Imager (GOCI)," Opt. Express 21, 3835-3849 (2013)

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  1. S. Cho, Y. H. Ahn, J. H. Ryu, G. Kang, and H. Youn, “Development of Geostationary Ocean Color Imager (GOCI),” Korean J. Remote Sens.26, 157–165 (2010).
  2. J. K. Choi, Y. J. Park, J. H. Ahn, H. S. Lim, J. Eom, and J. H. Ryu, “GOCI, the world's first geostationary ocean color observation satellite, for the monitoring of temporal variability in coastal water turbidity,” J. Geophys. Res.117(C9), C09004 (2012), doi:. [CrossRef]
  3. J. H. Ryu, J. K. Choi, J. Eom, and J. H. Ahn, “Temporal variation in Korean coastal waters using Geostationary Ocean Color Imager,” J. Coast. Res.64, 1731–1735 (2011).
  4. W. Shi and M. Wang, “Characterization of global ocean turbidity from Moderate Resolution Imaging Spectroradiometer ocean color observations,” J. Geophys. Res.115(C11), C11022 (2010), doi:. [CrossRef]
  5. W. Shi and M. Wang, “Satellite observations of the seasonal sediment plume in central East China Sea,” J. Mar. Syst.82(4), 280–285 (2010). [CrossRef]
  6. W. Shi and M. Wang, “Satellite views of the Bohai Sea, Yellow Sea, and East China Sea,” Prog. Oceanogr.104, 30–45 (2012). [CrossRef]
  7. M. Zhang, J. Tang, Q. Dong, Q. Song, and J. Ding, “Retrieval of total suspended matter concentration in the Yellow and East China Seas from MODIS imagery,” Remote Sens. Environ.114(2), 392–403 (2010). [CrossRef]
  8. W. Shi and M. Wang, “An assessment of the black ocean pixel assumption for MODIS SWIR bands,” Remote Sens. Environ.113(8), 1587–1597 (2009). [CrossRef]
  9. M. Wang, J. Tang, and W. Shi, “MODIS-derived ocean color products along the China east coastal region,” Geophys. Res. Lett.34(6), L06611 (2007), doi:. [CrossRef]
  10. A. Morel and B. Gentili, “Diffuse reflectance of oceanic waters: its dependence on Sun angle as influenced by the molecular scattering contribution,” Appl. Opt.30(30), 4427–4438 (1991). [CrossRef] [PubMed]
  11. H. R. Gordon, “Normalized water-leaving radiance: revisiting the influence of surface roughness,” Appl. Opt.44(2), 241–248 (2005). [CrossRef] [PubMed]
  12. M. Wang, “Effects of ocean surface reflectance variation with solar elevation on normalized water-leaving radiance,” Appl. Opt.45(17), 4122–4128 (2006). [CrossRef] [PubMed]
  13. IOCCG, Atmospheric correction for remotely-sensed ocean-colour products, M. Wang (Ed.), Reports of International Ocean-Color Coordinating Group, No. 10, IOCCG, Dartmouth, Canada (2010).
  14. R. P. Stumpf, R. A. Arnone, R. W. Gould, P. M. Martinolich, and V. Ransibrahmanakul, “A partially coupled ocean-atmosphere model for retrieval of water-leaving radiance from SeaWiFS in coastal waters,” (NASA Goddard Space Flight Center, Greenbelt, Maryland, 2003), pp. 51–59.
  15. S. W. Bailey, B. A. Franz, and P. J. Werdell, “Estimation of near-infrared water-leaving reflectance for satellite ocean color data processing,” Opt. Express18(7), 7521–7527 (2010). [CrossRef] [PubMed]
  16. K. G. Ruddick, F. Ovidio, and M. Rijkeboer, “Atmospheric correction of SeaWiFS imagery for turbid coastal and inland waters,” Appl. Opt.39(6), 897–912 (2000). [CrossRef] [PubMed]
  17. M. Wang, W. Shi, and J. Tang, “Water property monitoring and assessment for China's inland Lake Taihu from MODIS-Aqua measurements,” Remote Sens. Environ.115(3), 841–854 (2011). [CrossRef]
  18. M. Wang, “Remote sensing of the ocean contributions from ultraviolet to near-infrared using the shortwave infrared bands: simulations,” Appl. Opt.46(9), 1535–1547 (2007). [CrossRef] [PubMed]
  19. M. Wang, W. Shi, and L. Jiang, “Atmospheric correction using near-infrared bands for satellite ocean color data processing in the turbid western Pacific region,” Opt. Express20(2), 741–753 (2012). [CrossRef] [PubMed]
  20. J. H. Ahn, Y. J. Park, J. H. Ryu, B. Lee, and I. S. Oh, “Development of atmospheric correction algorithm for Geostationary Ocean Color Imager (GOCI),” Ocean Sci. J.47(3), 247–259 (2012). [CrossRef]
  21. M. Wang and W. Shi, “The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing,” Opt. Express15(24), 15722–15733 (2007). [CrossRef] [PubMed]
  22. M. Wang, S. Son, and W. Shi, “Evaluation of MODIS SWIR and NIR-SWIR atmospheric correction algorithm using SeaBASS data,” Remote Sens. Environ.113(3), 635–644 (2009). [CrossRef]
  23. M. Wang, “Aerosol polarization effects on atmospheric correction and aerosol retrievals in ocean color remote sensing,” Appl. Opt.45(35), 8951–8963 (2006). [CrossRef] [PubMed]
  24. M. Wang, “A refinement for the Rayleigh radiance computation with variation of the atmospheric pressure,” Int. J. Remote Sens.26(24), 5651–5663 (2005). [CrossRef]
  25. W. Shi and M. Wang, “Detection of turbid waters and absorbing aerosols for the MODIS ocean color data processing,” Remote Sens. Environ.110(2), 149–161 (2007). [CrossRef]
  26. M. Wang and W. Shi, “Cloud masking for ocean color data processing in the coastal regions,” IEEE Trans. Geosci. Rem. Sens.44(11), 3196–3205 (2006). [CrossRef]
  27. M. Wang and W. Shi, “Detection of ice and mixed ice-water pixels for MODIS ocean color data processing,” IEEE Trans. Geosci. Rem. Sens.47(8), 2510–2518 (2009). [CrossRef]
  28. M. Wang and W. Shi, “Sensor noise effects of the SWIR bands on MODIS-derived ocean color products,” IEEE Trans. Geosci. Rem. Sens.50(9), 3280–3292 (2012). [CrossRef]
  29. W. Shi and M. Wang, “Sea ice properties in the Bohai Sea measured by MODIS-Aqua: 1. Satellite algorithm development,” J. Mar. Syst.95, 32–40 (2012). [CrossRef]
  30. W. Shi and M. Wang, “Sea ice properties in the Bohai Sea measured by MODIS-Aqua: 2. Study of sea ice seasonal and interannual variability,” J. Mar. Syst.95, 41–49 (2012). [CrossRef]
  31. M. Wang, C. J. Nim, S. Son, and W. Shi, “Characterization of turbidity in Florida’s Lake Okeechobee and Caloosahatchee and St. Lucie estuaries using MODIS-Aqua measurements,” Water Res.46(16), 5410–5422 (2012). [CrossRef] [PubMed]
  32. H. R. Gordon, J. W. Brown, and R. H. Evans, “Exact Rayleigh scattering calculations for use with the Nimbus-7 Coastal Zone Color Scanner,” Appl. Opt.27(5), 862–871 (1988). [CrossRef] [PubMed]
  33. M. Wang, “The Rayleigh lookup tables for the SeaWiFS data processing: Accounting for the effects of ocean surface roughness,” Int. J. Remote Sens.23(13), 2693–2702 (2002). [CrossRef]
  34. M. Wang, “Atmospheric correction of ocean color sensors: Computing atmospheric diffuse transmittance,” Appl. Opt.38(3), 451–455 (1999). [CrossRef] [PubMed]
  35. H. Yang and H. R. Gordon, “Remote sensing of ocean color: assessment of water-leaving radiance bidirectional effects on atmospheric diffuse transmittance,” Appl. Opt.36(30), 7887–7897 (1997). [CrossRef] [PubMed]
  36. M. Wang, “A sensitivity study of SeaWiFS atmospheric correction algorithm: Effects of spectral band variations,” Remote Sens. Environ.67(3), 348–359 (1999). [CrossRef]
  37. M. Wang, S. Son, and J. L. W. Harding., “Retrieval of diffuse attenuation coefficient in the Chesapeake Bay and turbid ocean regions for satellite ocean color applications,” J. Geophys. Res.114(C10), C10011 (2009), doi:. [CrossRef]
  38. H. R. Gordon and M. Wang, “Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: a preliminary algorithm,” Appl. Opt.33(3), 443–452 (1994). [CrossRef] [PubMed]
  39. H. R. Gordon, “In-orbit calibration strategy for ocean color sensors,” Remote Sens. Environ.63(3), 265–278 (1998). [CrossRef]
  40. M. Wang and H. R. Gordon, “Calibration of ocean color scanners: How much error is acceptable in the near-infrared,” Remote Sens. Environ.82(2-3), 497–504 (2002). [CrossRef]
  41. B. A. Franz, S. W. Bailey, P. J. Werdell, and C. R. McClain, “Sensor-independent approach to the vicarious calibration of satellite ocean color radiometry,” Appl. Opt.46(22), 5068–5082 (2007). [CrossRef] [PubMed]
  42. M. Wang, K. D. Knobelspiesse, and C. R. McClain, “Study of the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) aerosol optical property data over ocean in combination with the ocean color products,” J. Geophys. Res.110(D10), D10S06 (2005), doi:. [CrossRef]
  43. J. E. Moon, Y. J. Park, J. H. Ryu, J. K. Choi, J. H. Ahn, J. E. Min, Y. B. Son, S. J. Lee, H. J. Han, and Y. H. Ahn, “Initial validation of GOCI water products against in situ data collected around Korean Peninsula for 2010–2011,” Ocean Sci. J.47(3), 261–277 (2012). [CrossRef]
  44. J. M. Mueller and G. S. Fargion, “Ocean optics protocols for satellite ocean color sensor validation, Revision 3, Part I & II,” (NASA Goddard Space Flight Center, Greenbelt, Maryland, 2002), pp. 1–308.
  45. S. W. Jeffrey and G. F. Humphrey, “New spectrophotometric equation for determining chlorophyll a, b, c1 and c2,” Biochem. Physiol. Pflanz.167, 194–204 (1975).
  46. J. E. O'Reilly, S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, and C. R. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res.103(C11), 24937–24953 (1998). [CrossRef]
  47. J. E. O'Reilly, S. Maritorena, D. A. Siegel, M. C. O'Brien, D. Toole, B. G. Mitchell, M. Kahru, F. P. Chavez, P. Strutton, G. F. Cota, S. B. Hooker, C. R. McClain, K. L. Carder, F. Muller-Karger, L. Harding, A. Magnuson, D. Phinney, G. F. Moore, J. Aiken, K. R. Arrigo, R. Letelier, and M. Culver, “Ocean color chlorophyll a algorithms for SeaWiFS, OC2 and OC4: Version 4,” (S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 2000), pp. 8–22.
  48. J. L. Mueller, “SeaWiFS algorithm for the diffuse attenuation coefficient, K(490), using water-leaving radiances at 490 and 555 nm,” (NASA Goddard Space Flight Center, Greenbelt, Maryland, 2000), pp. 24–27.
  49. A. Morel, Y. Huot, B. Gentili, P. J. Werdell, S. B. Hooker, and B. A. Franz, “Examining the consistency of products derived from various ocean color sensors in open ocean (Case 1) waters in the perspective of a multi-sensor approach,” Remote Sens. Environ.111(1), 69–88 (2007). [CrossRef]
  50. Z. P. Lee, M. Darecki, K. Carder, C. Davis, D. Stramski, and W. Rhea, “Diffuse attenuation coefficient of downwelling irradiance: An evaluation of remote sensing methods,” J. Geophys. Res.110(C2), C02017 (2005), doi:. [CrossRef]
  51. W. Shi, M. Wang, X. Li, and W. G. Pichel, “Ocean sand ridge signatures in the Bohai Sea observed by satellite ocean color and synthetic aperture radar measurements,” Remote Sens. Environ.115(8), 1926–1934 (2011). [CrossRef]
  52. G. Neukermans, K. G. Ruddick, and N. Greenwood, “Diurnal variability of turbidity and light attenuation in the southern North Sea from SEVIRI geostationary sensor,” Remote Sens. Environ.124, 564–580 (2012). [CrossRef]
  53. G. Dall'Olmo, E. Boss, M. J. Behrenfeld, T. K. Westberry, C. Courties, L. Prieur, M. Pujo-Pay, N. Hardman-Mountford, and T. Moutin, “Inferring phytoplankton carbon and eco-physiological rates from diel cycles of spectral particulate beam-attenuation coefficient,” Biogeosciences8(11), 3423–3439 (2011). [CrossRef]
  54. H. Loisel, V. Vantrepotte, K. Norkvist, X. Meriaux, M. Kheireddine, J. Ras, M. Pujo-Pay, Y. Combet, K. Leblanc, G. Dall'Olmo, R. Mauriac, D. Dessailly, and T. Moutin, “Characterization of the bio-optical anomaly and diurnal variability of particulate matter, as seen from scattering and backscattering coefficients, in ultra-oligotrophic eddies of the Mediterranean Sea,” Biogeosciences8(11), 3295–3317 (2011). [CrossRef]
  55. J. Neveux, C. Dupouy, J. Blanchot, A. L. Bouteiller, M. R. Landry, and S. L. Brown, “Diel dynamics of chlorophylls in high-nutrient, low-chlorophyll waters of the equatorial Pacific (180 degrees): Interactions of growth, grazing, physiological responses, and mixing,” J. Geophys. Res.108(C12), 8140 (2003), . [CrossRef]
  56. X. Guo and T. Yanagi, “Three-dimensional structure of tidal current in the East China Sea and Yellow Sea,” J. Oceanogr.54(6), 651–668 (1998). [CrossRef]
  57. T. Yanagi and K. Inoue, “Tide and tidal current in the Yellow/East China Seas,” Mer (Paris)32, 153–165 (1994).
  58. T. Yanagi, A. Morimoto, and K. Ichikawa, “Co-tidal and co-range charts for the East China Sea and the Yellow Sea derived from satellite altimetric data,” J. Oceanogr.53, 303–310 (1997).
  59. W. Shi, M. Wang, and L. Jiang, “Spring-neap tidal effects on satellite ocean color observations in the Bohai Sea, Yellow Sea, and East China Sea,” J. Geophys. Res.116(C12), C12032 (2011), doi:. [CrossRef]
  60. R. J. Uncles, J. A. Stephens, and R. E. Smith, “The dependence of estuarine turbidity on tidal intrusion length, tidal range and residence time,” Cont. Shelf Res.22(11-13), 1835–1856 (2002). [CrossRef]
  61. S. L. Yang, J. Zhang, and J. Zhu, “Response of suspended sediment concentration to tidal dynamics at a site inside the mouth of an inlet: Jiaozhou Bay (China),” Hydrol. Earth Syst. Sci.8(2), 170–182 (2004). [CrossRef]
  62. IOCCG, Ocean-colour observations from a geostationary orbit, D. Antoine (Ed.), Reports of International Ocean-Color Coordinating Group, No. 12, IOCCG, Dartmouth, Canada (2012).
  63. J. Fishman, L. T. Iraci, J. Al-Saadi, K. Chance, F. Chavez, M. Chin, P. Coble, C. Davis, P. M. DiGiacomo, D. Edwards, A. Eldering, J. Goes, J. Herman, C. Hu, D. J. Jacob, C. Jordan, S. R. Kawa, R. Key, X. Liu, S. Lohrenz, A. Mannino, V. Natraj, D. Neil, J. Neu, M. Newchurch, K. Pickering, J. Salisbury, H. Sosik, A. Subramaniam, M. Tzortziou, J. Wang, and M. Wang, “The United States' next generation of atmospheric composition and coastal ecosystem measurements: NASA's geostationary coastal and air pollution events (GEO-CAPE) mission,” Bull. Am. Meteorol. Soc.93(10), 1547–1566 (2012). [CrossRef]

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