The atmospheric correction procedure for CMODIS

Zhihua Mao; Delu Pan; Haiqing Huang

doi:10.1117/12.713271

28 October 2006 The atmospheric correction procedure for CMODIS

Zhihua Mao, Delu Pan, Haiqing Huang

Proceedings Volume 6419, Geoinformatics 2006: Remotely Sensed Data and Information; 64191V (2006) https://doi.org/10.1117/12.713271
Event: Geoinformatics 2006: GNSS and Integrated Geospatial Applications, 2006, Wuhan, China

Abstract

Ocean color satellites measure radiance at the top of atmosphere, while water-leaving radiance at sea surface is needed to derive ocean color information. It is necessary to develop atmospheric correction algorithms to obtain the water-leaving radiance from satellite-measured radiance. A kind of ocean color hyperspectral sensor called Chinese Moderate Resolution Imaging Spectrometer (CMODIS) on "Shenzhou-3" spaceship was launched on March 25, 2002. The CMODIS with 30 channels is much different with Sea-viewing Wide Field-of-view Sensor (SeaWiFS). The software of SeaWiFS Data Analysis System (SeaDAS) cannot be used to process the CMODIS data. A practical program was developed to implement the atmospheric correction procedure for CMODIS. The program can compute the Rayleigh scattering radiance and aerosol scattering radiance to deduce the water-leaving radiance. It considers the multiple-scattering effects and atmosphere absorbing effects on radiative transfer model. The results were compared with those by SeaDAS program at SeaWiFS bands to check the performance of the program. The water-leaving radiance deduced from in-situ measurements were also used to evaluate the accuracy of atmospheric correction algorithm and the mean relative error is 9.83%. The results show that this program is effective in processing CMODIS data and easily to be modified to process other kinds of satellite hyperspectral ocean color data.

Citation Download Citation

Zhihua Mao, Delu Pan, and Haiqing Huang "The atmospheric correction procedure for CMODIS", Proc. SPIE 6419, Geoinformatics 2006: Remotely Sensed Data and Information, 64191V (28 October 2006); https://doi.org/10.1117/12.713271

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