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Un modèle pour l'intégration spatiale et temporelle de données géolocalisées

Abstract : Earth Observation is a rapidly evolving domain. The European Space Agency recently launched the satellites of the Sentinel series, which will deliver between 8 and 10 TB of data per day, opening emerging opportunities in domains ranging from agriculture and environmental monitoring to urban planning, oceanography and climate studies. Domain-oriented applications require that images be enriched with data coming from various sources, that allow to better support decision-making processes related to the observed areas. One of the challenges to be addressed then concerns the integration of heterogeneous data. In this context, semantic technologies play a key role by providing an infrastructure based on standard models for representing data and on ontologies. We present a semantic approach to integrate data with the aim of enriching metadata of satellite imagery with data from various sources that are relevant to describe Earth observations for a particular need. We propose a semantic vocabulary, a forma-lization of spatio-temporal relationships as well as an integration process of various geo-spatial data sets. We illustrate our approach through a case study exploiting meteorological data.
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Contributor : Nathalie Aussenac-Gilles <>
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Helbert Arenas, Cassia Trojahn dos Santos, Catherine Comparot, Nathalie Aussenac-Gilles. Un modèle pour l'intégration spatiale et temporelle de données géolocalisées. Revue Internationale de Géomatique, Lavoisier, 2018, 28 (2), pp.243-266. ⟨10.3166/rig.2018.00055⟩. ⟨hal-02398679⟩



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