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A Layer Removal Scheme for Atmospheric Correction of Satellite Ocean Color Data in Coastal Regions

Authors :
Bangyi Tao
Jianyu Chen
Zengzhou Hao
Peng Chen
Qiankun Zhu
Haiqing Huang
Zhihua Mao
Source :
IEEE Transactions on Geoscience and Remote Sensing. 59:1382-1391
Publication Year :
2021
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2021.

Abstract

The radiance received by satellite sensors viewing the ocean is a mixed signal of the atmosphere and ocean. Accurate decomposition of the radiance components is crucial because any inclusion of atmospheric signal in the water-leaving radiance leads to an incorrect estimation of the oceanic parameters. This is especially true over the turbid coastal waters, where the estimation of the radiance components is difficult. A layer removal scheme for atmospheric correction (LRSAC) has been developed to take the atmospheric and oceanic components as the layer structure according to the sunlight passing in the Sun–Earth-satellite system. Compared with the normal coupled atmospheric column, the uncertainty of the layer structure of Rayleigh and aerosols has a relatively small error with a mean relative error (MRE) of 0.063%. As the aerosol layer was put between Rayleigh and ocean, a new Rayleigh lookup table (LUT) was regenerated using 6SV (Second Simulation of a Satellite Signal in the Solar Spectrum, Vector version 3.2) based on the zero reflectance at the ground to produce the pure Rayleigh reflectance without the Rayleigh–ocean interaction. The accuracy of the LRSAC was validated by in situ water-leaving reflectance, obtaining an MRE of 6.3%, a root-mean-square error (RMSE) of 0.0028, and the mean correlation coefficient of 0.86 based on 430 matchup pairs over the East China Sea. Results show that the LRSAC can be used to decompose the reflectance at the top of each layer for the atmospheric correction over turbid coastal waters.

Details

ISSN :
15580644 and 01962892
Volume :
59
Database :
OpenAIRE
Journal :
IEEE Transactions on Geoscience and Remote Sensing
Accession number :
edsair.doi...........8ca81c69e7378c0709076db0cad68631