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

Research output: Book chapterConference contributionpeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationInformation Processing and Management of Uncertainty in Knowledge-Based Systems - 15th International Conference, IPMU 2014, Proceedings
PublisherSpringer Verlag
Pages97-106
Number of pages10
EditionPART 1
ISBN (Print)9783319087948
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event15th International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems, IPMU 2014 - Montpellier, France
Duration: 15 Jul 201419 Jul 2014

Publication series

NameCommunications in Computer and Information Science
NumberPART 1
Volume442 CCIS
ISSN (Print)1865-0929

Conference

Conference15th International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems, IPMU 2014
Country/TerritoryFrance
CityMontpellier
Period15/07/1419/07/14

Keywords

  • Data Mining and Remote Sensing
  • Temporal Patterns

Fingerprint

Dive into the research topics of 'Towards the Use of Sequential Patterns for Detection and Characterization of Natural and Agricultural Areas'. Together they form a unique fingerprint.

Cite this