DocumentCode :
532281
Title :
Aerosol retrieval from remote sensing image using artificial neural network
Author :
Wang, Houmao ; Tang, Jiakui
Author_Institution :
Yantai Inst. of Coastal Zone Res., Chinese Acad. of Sci., Yantai, China
Volume :
5
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
The usual method of aerosol retrieval using remote sensing is interpolation of look-up-table (LUT), but it is too time-consuming. However, artificial neural network for nonlinear problem has been not applied widely for aerosol retrieval before. In this paper, aerosol optical depth (AOD) is retrieved using two methods: interpolation and neural network. Then, the retrieval capabilities of the two methods were compared. By comparison, not only is the retrieval error of the neural network within acceptable range, but also it can reduce much processing time.
Keywords :
aerosols; artificial intelligence; atmospheric techniques; geophysical image processing; image retrieval; interpolation; neural nets; remote sensing; table lookup; LUT; aerosol optical depth; aerosol retrieval; artificial neural network; interpolation; look-up-table; nonlinear problem; remote sensing image; Atmospheric measurements; Data models; Measurement uncertainty; Neurons; Particle measurements; Table lookup; Aerosol optical depth; artificial neural network; interpolation; look-uptables; remote sensing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5620271
Filename :
5620271
Link To Document :
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