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Remote Sensing Technology and Application  2014, Vol. 29 Issue (5): 795-802    DOI: 10.11873/j.issn.1004-0323.2014.5.0795
    
Study on Method and Experiment of Hyper\|spectral Atmospheric Infrared Sounder Channel Selection
Wang Gen1,Lu Qifeng2,Zhang Jianwei3,Wen Huayang1
(1.Anhui Meteorological Information Centre,Hefei 230031,China;
2.National Satellite Meteorological Centers,China Meteorological Administration,Beijing 100081,China;3.College of Mathematics and Statistics,Nanjing University of Information Science & Technology,Nanjing 210044,China)
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Abstract  

Considering the correlation between channels of hyper\|spectral atmospheric infrared sounder,as well as the timeliness of variational assimilation,channel selection is necessary.The principal component\|stepwise regression method is adopted for AIRS channel selection in this paper.Due to the fact that CO2 short wave channel easily affected by sunlight during the day,this study consider the channel combination during daytime and nighttime respectively.In the process of specific implementation:First,the channels are pre\|processed.Then,the principal components of Jacobi matrix about the temperature and humidity are analyzed respectively and some principal components with great effects are selected.By using the stepwise regression method,the channels with great affect on principal components are selected to form a channel subset.Further,according to the experience and actual observation data,principal components dual\|zone regression method is adopted for channel selection,in order to make an achievement of optimizing the global and take the local into account,with the idea of partition.Research results indicate that:①it is very necessary to rationally choose the channels when retrieves atmospheric temperature and humidity with AIRS data;② The channel combination obtains from principal components dual\|zone regression,and retrieving atmospheric temperature and humidity error are smaller than iterative method based on information entropy as a whole.

Key words:  Hyper-spectral      Channel selection      Jacobi matrix      Principal components-stepwise regression     
Received:  08 April 2013      Published:  10 November 2014
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Wang Gen
Lu Qifeng
Zhang Jianwei
Wen Huayang

Cite this article: 

Wang Gen,Lu Qifeng,Zhang Jianwei,Wen Huayang. Study on Method and Experiment of Hyper\|spectral Atmospheric Infrared Sounder Channel Selection. Remote Sensing Technology and Application, 2014, 29(5): 795-802.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2014.5.0795     OR     http://www.rsta.ac.cn/EN/Y2014/V29/I5/795

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