
Proceedings Paper
Improved topographic correction approach for radiation of remote sensing imageFormat | Member Price | Non-Member Price |
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Paper Abstract
Remote sensing images of rugged areas are severely affected by the topographic effects. Usually, the effects can cause
plenty of shades in the images and result in a high variation in the reflectance response for similar vegetation types.
Accordingly, these effects will strongly affect the quality of vegetation classification. In general, the irradiance which a
slope accepts contains three parts: the direct solar irradiance, the diffuse sky irradiance and the irradiance from adjacent
terrain. But the area facing away from the sun cannot accept the direct solar irradiance. The C correction method which
takes into accounts the effects of the atmosphere and adjacent terrain has become a popular method for topographic
correction. But the C corrected image has a problem of overcorrection, especially in the area of high incidence angles,
since this method is based on the empirical linear correlation between observed radiance and the cosine values of solar
incidence angles. In this paper, an improved C correction method is proposed to reduce this error and improve the
accuracy of classification.
Paper Details
Date Published: 14 November 2007
PDF: 7 pages
Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67902O (14 November 2007); doi: 10.1117/12.750971
Published in SPIE Proceedings Vol. 6790:
MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications
Yongji Wang; Jun Li; Bangjun Lei; Chao Wang; Liang-Pei Zhang; Jing-Yu Yang, Editor(s)
PDF: 7 pages
Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67902O (14 November 2007); doi: 10.1117/12.750971
Show Author Affiliations
Shumin Liu, Univ. of Electronic Science and Technology of China (China)
Institute of Remote Sensing Applications (China)
Xingfa Gu, Univ. of Electronic Science and Technology of China (China)
Institute of Remote Sensing Applications (China)
Hongyou Liang, Institute of Remote Sensing Applications (China)
Institute of Remote Sensing Applications (China)
Xingfa Gu, Univ. of Electronic Science and Technology of China (China)
Institute of Remote Sensing Applications (China)
Hongyou Liang, Institute of Remote Sensing Applications (China)
Feiming Wei, Univ. of Electronic Science and Technology of China (China)
Institute of Remote Sensing Applications (China)
Yang Dong, Univ. of Electronic Science and Technology of China (China)
Institute of Remote Sensing Applications (China)
Institute of Remote Sensing Applications (China)
Yang Dong, Univ. of Electronic Science and Technology of China (China)
Institute of Remote Sensing Applications (China)
Published in SPIE Proceedings Vol. 6790:
MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications
Yongji Wang; Jun Li; Bangjun Lei; Chao Wang; Liang-Pei Zhang; Jing-Yu Yang, Editor(s)
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