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Evaluation of GOCI sensitivity for At-Sensor radiance and GDPS-Retrieved chlorophyll-a products

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Abstract

The signal-to-noise ratio (SNR, or sensitivity) of an ocean color instrument is a critical parameter to determine the accuracy and precision of the data products. Yet published literature showed various formats in SNR specifications under different conditions, making a direct cross-sensor comparison difficult. Here, we compared the SNRs of GOCI spectral bands with those of SeaWiFS and MODIS/Aqua under the same radiance inputs. We also compared their ability to resolve small changes in the retrieved chlorophyll-a data products (Chl). While GOCI visible bands showed similar at-sensor SNRs to SeaWiFS, the near-infrared (NIR) bands showed significantly higher SNRs. Because the NIR bands were used for atmospheric correction, the increases in SNRs led to reduced noise in the retrieved Chl, as shown in the GOCI and SeaWiFS Chl products for Chl < 0.1 mg m−3. The noise in the retrieved products also depends on the retrieval algorithms in addition to the sensor SNR. When a new band-subtraction algorithm (the Ocean Color Index or OCI algorithm) was applied to the same GOCI remotesensing reflectance data derived from the GDPS software package, significant noise reduction was found in the Chl product for low concentrations (< 0.25 mg m−3), leading to product precision (∼3% in Chl) comparable to those from MODIS/Aqua measurements. This is certainly a significant achievement, as GOCI spatial resolution is much higher than MODIS (500 m versus 1 km). In addition, artifacts across image mosaic edges over low-concentration waters have been removed nearly completely by the OCI algorithm. Data analyses also indicated that GOCI radiometric calibration requires further improvement.

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References

  • Gordon HR, Clark DK (1981) Clear water radiances for atmospheric correction of coastal zone color scanner imagery. Appl Optics 20:4175–4180

    Article  Google Scholar 

  • Gordon HR, Wang M (1994) Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: A preliminary algorithm. Appl Optics 33:443–452

    Article  Google Scholar 

  • Hu C, Carder KL, Muller-Karger FE (2001a) How precise are SeaWiFS ocean color estimates? Implications of digitization-noise errors. Remote Sens Environ 76:239–249

    Article  Google Scholar 

  • Hu C, Feng L, Lee Z, Davis C, Mannino A, McClain C, Franz B (2012b) Dynamic range and sensitivity requirements of satellite ocean color sensors: Learning from the past. Appl Optics 51:6045–6062

    Article  Google Scholar 

  • Hu C, Lee Z, Franz B (2012a) Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference. J Geophys Res 117:C01011

    Article  Google Scholar 

  • Hu C, Muller-Karger FE, Andrefouet S, Carder KL (2001b) Atmospheric correction and cross-calibration of LANDSAT-7/ETM+ imagery over aquatic environments: A multiplatform approach using SeaWiFS/MODIS. Remote Sens Environ 78:99–107

    Article  Google Scholar 

  • Morel A, Maritorena S (2001) Bio-optical properties of oceanic waters: A reappraisal. J Geophys Res 106:7163–7180

    Article  Google Scholar 

  • O’Reilly J, Maritorena S, Siegel D, O’Brien M, Toole D, Mitchell B, Kahru M, Chavez F, Strutton P, Cota G, Hooker S, McClain C, Carder K, Muller-Karger F, Harding L, Magnuson A, Phinney D, Moore G, Aiken J, Arrigo K, Letelier R, Culver M (2000) SeaWiFS Postlaunch Calibration and Validation Analyses, Part 3, NASA Tech Memo. In: Hooker S, Firestone E (eds) NASA Goddard Space Flight Center, Greenbelt, MD, pp 49

    Google Scholar 

  • Pan D, He X, Zhu Q (2004) In-orbit cross-calibration of HY-1A satellite sensor COCTS. Chinese Sci Bull 49:2521–2526

    Google Scholar 

  • Ryu J-H, Han H-J, Cho S, Park Y-J, Ahn Y-H (2012) Overview of Geostationary Ocean Color Imager (GOCI) and GOCI Data Processing System(GDPS). Ocean Sci J (in the issue)

  • Wang M, Franz BA (2000) Comparing the ocean color measurements between MOS and SeaWiFS: A vicarious intercalibration approach for MOS. IEEE Trans Geosci Remote Sens 38:184–197

    Article  Google Scholar 

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Hu, C., Feng, L. & Lee, Z. Evaluation of GOCI sensitivity for At-Sensor radiance and GDPS-Retrieved chlorophyll-a products. Ocean Sci. J. 47, 279–285 (2012). https://doi.org/10.1007/s12601-012-0028-0

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  • DOI: https://doi.org/10.1007/s12601-012-0028-0

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