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S2PViewer : un prototype de visualisation de motifs spatio-temporels

Abstract : The volume of stored data in spatiotemporal databases increases rapiditly. It becomes crucial to provide summaries from these data allow experts to make decisions and to act immediately on the results. In this context, spatial data mining, which helps to identify new patterns in these databases coupled with visualization methods, facilitates the work of experts. Visualization derived from data mining can provide great add value, often crucial for the understanding of some spatiotemporal dynamics. In this paper, we present a new visualization approach of spatiotemporal patterns. Our proposition has been tested on a database containing information about epidemiological surveillance of dengue in New Caledonia.
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Conference papers
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Contributor : Migration Irstea Publications <>
Submitted on : Tuesday, September 29, 2020 - 10:37:56 AM
Last modification on : Monday, November 30, 2020 - 2:40:02 PM
Long-term archiving on: : Wednesday, December 30, 2020 - 6:18:19 PM


  • HAL Id : hal-02599582, version 1
  • IRSTEA : PUB00040588


Hugo Alatrista Salas, Sandra Bringay, Frédéric Flouvat, Nazha Selmaoui-Folcher, Maguelonne Teisseire. S2PViewer : un prototype de visualisation de motifs spatio-temporels. Conférence Internationale de Géomatique et d’analyse spatiale (SAGEO), Sep 2013, Brest, France. ⟨hal-02599582⟩



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