neural network, QAA, residual error, SeaWiFS, inherent optical properties, OCI
Digital Object Identifier (DOI)
An approach to semianalytically derive waters' inherent optical properties (IOPs) from remote sensing reflectance (Rrs) and at the same time to take into account the residual errors in satellite Rrs is developed for open-ocean clear waters where aerosols are likely of marine origin. This approach has two components: (1) a scheme of combining a neural network and an algebraic solution for the derivation of IOPs, and (2) relationships between Rrs residual errors at 670 nm and other spectral bands. This approach is evaluated with both synthetic and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data, and the results show that it can significantly reduce the effects of residual errors in Rrs on the retrieval of IOPs, and at the same time remove partially the Rrs residual errors for “low-quality” and “high-quality” data defined in this study. Furthermore, more consistent estimation of chlorophyll concentrations between the empirical blue-green ratio and band-difference algorithms can be derived from the corrected “low-quality” and “high-quality” Rrs. These results suggest that it is possible to improve both data quality and quantity of satellite-retrieved Rrs over clear open-ocean waters with a step considering the spectral relationships of the residual errors in Rrs after the default atmospheric correction procedure and without fixing Rrs at 670 nm to one value for clear waters in a small region such as 3 × 3 box.
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Citation / Publisher Attribution
Journal of Geophysical Research: Oceans, v. 121, issue 6, p. 3866-3886
©2016. American Geophysical Union. All Rights Reserved.
Scholar Commons Citation
Chen, Jun; Lee, Zhongping; Hu, Chuanmin; and Wei, Jianwei, "Improving Satellite Data Products for Open Oceans with a Scheme to Correct the Residual Errors in Remote Sensing Reflectance" (2016). Marine Science Faculty Publications. 1961.