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- Title
Deriving colored dissolved organic matter absorption coefficient from ocean color with a neural quasi-analytical algorithm.
- Authors
Chen, Jun; He, Xianqiang; Zhou, Bin; Pan, Delu
- Abstract
The objective of this study is to develop an approach to estimate the gelbstoff absorption coefficient ( ag) from remote sensing reflectance ( Rrs). This approach includes two components: the inherent optical properties are semianalytically derived from the Rrs by a neural quasianalytical algorithm (NQAA), and then the derivations are semianalytically extended to ag estimations using a band difference approach. This method is then evaluated with the various type of ocean color data including synthetic, field measured, and satellite-observed data. The results show that the method can produce an excellent quantitative agreement between the estimated and known ag in ocean waters with a wide range of optical properties, while significantly reducing the effects of residual error in SeaWiFS Rrs, primarily from the imperfect atmospheric correction algorithm on the retrieval of ag in the clear open oceans. Furthermore, with the application of this new algorithm, the SeaWiFS ag products exhibit more spatially and temporally uniform results than the band ratio approach-based ag retrieval algorithm. These results indicate that the new algorithm is an encouraging approach to process ocean color images for ag retrieval, although a greater number of independent tests with in situ and satellite data are required to further validate and improve this approach.
- Publication
Journal of Geophysical Research. Oceans, 2017, Vol 122, Issue 11, p8543
- ISSN
2169-9275
- Publication type
Article
- DOI
10.1002/2017JC013115