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