DocumentCode :
3598087
Title :
An improved spectral knowledge for multi-temporal images classification-a case study of urban area
Author :
Liu, C.-H. ; Chen, A.J.
Author_Institution :
Center for Space & Remote Sensing Res., Nat. Central Univ., Chung-Li, Taiwan
Volume :
2
fYear :
34881
Firstpage :
1279
Abstract :
The authors demonstrate that the normalized reflectance is much more suitable than bidirectional reflectance factor (BRF) as the scene-independent spectral knowledge as Wharton (1987) suggested. Normalized reflectance can be obtained from normalization of BRF by its intrinsic BRDF. Transformed divergences of apparent reflectance, BRF and normalized reflectance of the urban target in the multi-temporal dataset are compared
Keywords :
geophysical signal processing; geophysical techniques; image classification; image sequences; optical information processing; remote sensing; BRDF; BRF; apparent reflectance; bidirectional reflectance factor; divergence; geophysical measurement technique; image sequences; land surface; multi-temporal image classification; multispectral remote sensing; normalized reflectance; optical imaging; scene-independent spectral knowledge; spectral knowledge; terrain mapping; urban area; visible IR infrared; Aerosols; Atmosphere; Atmospheric modeling; Bidirectional control; Computer aided software engineering; Image classification; Parametric statistics; Reflectivity; Remote sensing; Satellites;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1995. IGARSS '95. 'Quantitative Remote Sensing for Science and Applications', International
Print_ISBN :
0-7803-2567-2
Type :
conf
DOI :
10.1109/IGARSS.1995.521725
Filename :
521725
Link To Document :
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