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EARSeL: 2nd Workshop on Remote Sensing of the Coastal Zone Porto, Portugal, 9-11 June 2005 |
SESSION PA2 OCEAN COLOUR |
Joo-Hyung Ryu, Shanmugam P., Yu-Hwan Ahn
Satellite Ocean Research Lab., KORDI,
Ansan P.O. Box 29, Seoul 425-600, Korea
jhryu@kordi.re.kr
Application of the Landsat signal over aquatic environment requires the retrieval of water-leaving radiance (Lw) from the total radiance recorded at the top-of-the-atmosphere (TOA) and thus of the water constituents’ of interest. Retrieval of Lw from the TOA signal using a certain algorithm is referred to as the atmospheric correction, which over aquatic environment is more demanding than over land because the signal from the water column is small and it carries immense information about biogeochemical variables in the ocean. This paper describes methods for the correction of the atmospheric effects in the Landsat visible and near-infrared (VIS/NIR) imagery in relation to the retrieval of meaningful information about the ocean colour, especially from Case-II waters around the Korean peninsula. Two atmospheric correction (AC) methods implemented and examined, using the TOA radiance or reflectance data, are spectral shape matching (SSMM) and path extraction methods. The path-extraction assumes that the total radiance (LTOA) of a pixel of the black ocean in a given image is considered as the path signal, which remains constant over, at least, the sub scene of Landsat VIS/NIR imagery. The assumption of SSMM is nearly similar, but it does extract the path signal from the LTOA by matching-up the in situ data of water-leaving radiance, for typical clear and turbid waters, and extrapolate it to be the spatially homogeneous contribution of the scattered signal after complex interaction of light with atmospheric aerosols and Raleigh particles, and direct reflection of light on the sea surface. The overall shape and magnitude of radiance or reflectance spectra of the atmospherically corrected Landsat VIS/NIR imagery by SSMM appears to have very good agreement with the in situ spectra collected for clear and turbid waters, while path-extraction over turbid waters though often reproduces in situ spectra, but yields significant errors for clear waters due to the invalid assumption of zero water-leaving radiance for the black ocean pixels. Validation suggests that the accurate retrieval of water-leaving radiance is not feasible with the invalid assumption of the classical AC algorithms, but is feasible with SSMM. The goal of performing the atmospheric correction with SSMM to estimate suspended sediment (SS) concentration, using Landsat TM/ETM+ SS algorithm, has also been demonstrated on the Landsat TM/ETM+ imagery acquired over the highly turbid Wan-do, Jin-do bays and Saemanguem area of Korea.
Last Update: 2005-03-16