Radiance transformation of multitemporal LANDSAT image for land cover classification

Fumihiro Tanizaki*, Michiharu Niimi, Sei ichiro Kamata, Eiji Kawaguchi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSociety of Photo-Optical Instrumentation Engineers
Number of pages8
ISBN (Print)0819418587
Publication statusPublished - 1995 Jan 1
Externally publishedYes
EventVisual Communications and Image Processing '95 - Taipei, Taiwan
Duration: 1995 May 241995 May 26

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherVisual Communications and Image Processing '95
CityTaipei, Taiwan

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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