Towards the Use of Sequential Patterns for Detection and Characterization of Natural and Agricultural Areas

  • Fabio Guttler
  • Dino Ienco
  • Maguelonne Teisseire
  • Jordi Nin
  • Pascal Poncelet
Part of the Communications in Computer and Information Science book series (CCIS, volume 442)


Nowadays, a huge amount of high resolution satellite images are freely available. Such images allow researchers in environmental sciences to study the different natural habitats and farming practices in a remote way. However, satellite images content strongly depends on the season of the acquisition. Due to the periodicity of natural and agricultural dynamics throughout seasons, sequential patterns arise as a new opportunity to model the behaviour of these environments. In this paper, we describe some preliminary results obtained with a new framework for studying spatiotemporal evolutions over natural and agricultural areas using k-partite graphs and sequential patterns extracted from segmented Landsat images.


Temporal Patterns Data Mining and Remote Sensing 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Fabio Guttler
    • 1
  • Dino Ienco
    • 1
  • Maguelonne Teisseire
    • 1
  • Jordi Nin
    • 2
  • Pascal Poncelet
    • 3
  1. 1.IRSTEA, UMR TETISMontpellierFrance
  2. 2.Barcelona Supercomputing Center (BSC)Universitat Politècnica de Catalunya (BarcelonaTech)BarcelonaSpain
  3. 3.LIRMM, CNRSMontpellierFrance

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