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| Titel |
CAAS: an atmospheric correction algorithm for the remote sensing of complex waters |
| VerfasserIn |
P. Shanmugam |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
0992-7689
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| Digitales Dokument |
URL |
| Erschienen |
In: Annales Geophysicae ; 30, no. 1 ; Nr. 30, no. 1 (2012-01-18), S.203-220 |
| Datensatznummer |
250017174
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| Publikation (Nr.) |
 copernicus.org/angeo-30-203-2012.pdf |
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| Zusammenfassung |
| The current SeaDAS atmospheric correction algorithm relies on the computation
of optical properties of aerosols based on radiative transfer combined with
a near-infrared (NIR) correction scheme (originally with assumptions of zero
water-leaving radiance for the NIR bands) and several ancillary parameters
to remove atmospheric effects in remote sensing of ocean colour. The failure
of this algorithm over complex waters has been reported by many recent
investigations, and can be attributed to the inadequate NIR correction and
constraints for deriving aerosol optical properties whose characteristics
are the most difficult to evaluate because they vary rapidly with time and
space. The possibility that the aerosol and sun glint contributions can be
derived in the whole spectrum of ocean colour solely from a knowledge of the
total and Rayleigh-corrected radiances is developed in detail within the
framework of a Complex water Atmospheric correction Algorithm Scheme (CAAS)
that makes no use of ancillary parameters. The performance of the CAAS
algorithm is demonstrated for MODIS/Aqua imageries of optically complex
waters and yields physically realistic water-leaving radiance spectra that
are not possible with the SeaDAS algorithm. A preliminary comparison with
in-situ data for several regional waters (moderately complex to clear
waters) shows encouraging results, with absolute errors of the CAAS
algorithm closer to those of the SeaDAS algorithm. The impact of the
atmospheric correction was also examined on chlorophyll retrievals with a
Case 2 water bio-optical algorithm, and it was found that the CAAS algorithm
outperformed the SeaDAS algorithm in terms of producing accurate pigment
estimates and recovering areas previously flagged out by the later
algorithm. These findings suggest that the CAAS algorithm can be used for
applications focussing in quantitative assessments of the biological and
biogeochemical properties in complex waters, and can easily be extended to
other sensors such as OCM-2, MERIS and GOCI. |
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