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Mining Sequential Patterns from MODIS Time Series for Cultivated Area Mapping

  • Yoann PitarchEmail author
  • Elodie Vintrou
  • Fadi Badra
  • Agnès Bégué
  • Maguelonne Teisseire
Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC, volume 1)

Abstract

To predict and respond to famine and other forms of food insecurity, different early warning systems are using remote analyses of crop condition and agricultural production by using satellite-based information. To improve these predictions, a reliable estimation of the cultivated area at a national scale must be carried out. In this study, we developed a data mining methodology for extracting cultivated domain patterns based on their temporal behavior as captured in time-series of moderate resolution remote sensing MODIS images.

Keywords

Sequential Pattern Early Warning System Numerical Attribute Mining Sequential Pattern Representative Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Yoann Pitarch
    • 1
    Email author
  • Elodie Vintrou
    • 2
    • 4
  • Fadi Badra
    • 3
    • 4
  • Agnès Bégué
    • 2
    • 4
  • Maguelonne Teisseire
    • 3
    • 4
  1. 1.LIRMM - CNRS - UM2MontpellierFrance
  2. 2.CIRADMontpellierFrance
  3. 3.CemagrefMontpellierFrance
  4. 4.TETISMontpellierFrance

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