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Proceedings Paper

Radiance transformation of multitemporal LANDSAT image for land cover classification
Author(s): Fumihiro Tanizaki; Michiharu Niimi; Sei-ichiro Kamata; Eiji Kawaguchi
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Paper Abstract

Recently classification of remote sensing images using neural network approach is studied. However multitemporal LANDSAT image data is not used for classification. A problem in classification of remote sensing images is that we cannot get images in fixed wide area such as states of prefectures at one time because the range of sensors of artificial satellite is limited. For example, full area of Fukuoka prefecture is observed two separate images. For multitemporal images, several factors affect the spectrum at different observation dates. In this paper, we concentrate on the sunbeam factor from which we can estimate the intensity. Using the sun elevation angle from the data, we can estimate sunbeam intensity. We transform multitemporal images using radiance transformation which is based on path radiance model. We confirmed that radiance transformation is effective to the classification of multitemporal images from several experiments.

Paper Details

Date Published: 21 April 1995
PDF: 8 pages
Proc. SPIE 2501, Visual Communications and Image Processing '95, (21 April 1995); doi: 10.1117/12.206704
Show Author Affiliations
Fumihiro Tanizaki, Kyushu Institute of Technology (Japan)
Michiharu Niimi, Nagasaki Institute of Applied Science (Japan)
Sei-ichiro Kamata, Kyushu Institute of Technology (Japan)
Eiji Kawaguchi, Kyushu Institute of Technology (Japan)


Published in SPIE Proceedings Vol. 2501:
Visual Communications and Image Processing '95
Lance T. Wu, Editor(s)

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