On mining METEOSAT and ERS multitemporal images

نویسندگان

  • Andreea Julea
  • Nicolas Méger
  • Emmanuel Trouvé
چکیده

The frequency and the resolution of the images acquired by remote sensing techniques are nowadays so high that end-users can get huge volumes of observation data for a same geographic area. In this paper, we propose to use data mining tools for detecting evolutions. More precisely, we explain how to make use of sequential patterns to automatically extract evolutions that are contained in a satellite images series which is considered as a base of sequences. Experiments on optical data from METEOSAT satellite and on Synthetic Aperture Radar (SAR) images from European Remote Sensing (ERS) satellites are presented.

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تاریخ انتشار 2006