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