Author(s): Helbert Arenas, Nathalie Aussenac-Gilles, Catherine Comparot, Cassia Trojahn
Abstract: Earth observation is a rapidly evolving domain. Recently launched satellites, which deliver between 8 and 10TB of image data per day, open emerging opportunities in domains ranging from environmental monitoring to urban planning and climate studies. However, domain-oriented applications require raw image metadata to be enriched with data coming from various sources (either static or dynamic), in order to support decision-making processes related to the observed areas. One of challenges to be addressed concerns the integration of heterogeneous data highly relying on spatio-temporal representations. This paper presents a semantic approach to integrate data with the aim of enriching metadata of satellite imagery with various open data sets that are relevant to describe Earth Observations for a particular need. We propose a semantic vocabulary that specializes standards (like SOSA, GeoSPARQL) as well as a process – based on spatial and temporal features – to select, map and integrate heterogeneous geo-spatial data sets. This process relies on image tiles to handle data with a fixed spatial component while the temporal relationships are calculated on the fly based on temporal topology.
Keywords: earth observation data; satellite imagery; semantic integration; vocabularies and ontologies; Ontology-based Data Integration