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Vicarious Calibration of GOCI for the SeaDAS Ocean Color RetrievalA key on-orbit calibration step for satellite remote sensing of ocean color is the vicarious calibration. This establishes the final gains for each spectral band on the sensor that minimize bias in the retrieved ocean color signal. The vicarious calibration is specific to the instrument and the atmospheric correction algorithm. The vicarious calibration gains for the Geostationary Ocean Color Imager (GOCI) are presented here, which were derived to optimize the performance ofNASA's standard atmospheric correction algorithm as implemented in the l2gen code and distributed through the SeaDAS open-source software package. Following NASA's protocols, the near-infrared(NIR) bands were calibrated first, and the visible bands were then calibrated relative to this fixed NIR calibration. The gain for the 745-nm NIR band was derived using a fixed aerosol model, which waschosen based on the Angstrom Coefficients derived from MODIS onAqua (MODISA). For the vicarious gains of the visible bands, twosources for the target water-leaving radiances were tested: matchupsfrom MODISA and climatological data from SeaWiFS. A validation analysis using AERONET-OC data shows an improvement in sensor performance when compared with results using the current vicarious gains and results using no vicarious calibration. Good agreement was found in vicarious gains derived using both concurrent MODISA and climatological SeaWiFS as vicarious calibration data sources. These results support the use of a concurrent sensor for the vicarious calibration when in situ data are not available and demonstrate that using climatology from a well-calibrated sensor like SeaWiFSfor the vicarious calibration is a valid alternative when it is not possible to use a concurrent sensor or in situ data. We recommend using the gains derived from concurrent GOCI matchups with MODISA for GOCI processing in SeaDAS/l2gen.
Document ID
20190001714
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Concha, Javier
(Universities Space Research Association (USRA) Columbia, MD, United States)
Mannino, Antonio
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Franz, Bryan
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Bailey, Sean
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Kim, Wonkook
(Korean Inst. of Ocean Science and Technology (KIOST) Ansan, South Korea, Republic of)
Date Acquired
March 20, 2019
Publication Date
January 7, 2019
Publication Information
Publication: International Journal of Remote Sensing
Publisher: Taylor & Francis
ISSN: 0143-1161
e-ISSN: 1366-5901
Subject Category
Earth Resources And Remote Sensing
Oceanography
Report/Patent Number
GSFC-E-DAA-TN65760
ISSN: 0143-1161
Report Number: GSFC-E-DAA-TN65760
E-ISSN: 1366-5901
Funding Number(s)
CONTRACT_GRANT: NNH12ZDA001N-ESUSPI
Distribution Limits
Public
Copyright
Other

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