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6 August 2018 A semantic representation of EO data for image retrieval based on natural language queries
Marco Polignano, Marco de Gemmis, Vasilis Kopsacheilis, Michail Vaitis, Jenny Malig, Dominik Grether, Ilias Ioannou, Anastasia Sarelli, Vito De Pasquale, Sergio Samarelli, Pol Kolokoussis, Kleanthis Karamvasis, Milto Miltiadou, Christiana Papoutsa, Olivier Regniers, Virginie Lafon, Konstantinos Topouzelis , Bogdan Despotov
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Proceedings Volume 10773, Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018); 1077306 (2018) https://doi.org/10.1117/12.2325839
Event: Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), 2018, Paphos, Cyprus
Abstract
SEO-DWARF (Semantic Earth Observation Data Web Alert and Retrieval Framework) is a project funded by the European Union Horizon 2020 research and innovation programme. The main objective of the project is to realize the content-based search of Earth Observation (EO) images on an application specific basis. The satellite images, which come from EO satellites such as Sentinels 1, 2 and 3, as well as ENVISAT, are distributed with few correlated meta-data which do not describe the phenomena and the objects included in the image. Innovative approaches to process remote sensing images can extract relevant information which semantically describes the land type, the region area border, objects and events such as oil spill. This information can be modeled as structured information through ontologies to be processed by algorithms to perform information retrieval and filtering. The proposed system is aware of the semantic elements which are relevant for final user and will be able to answer natural language queries such as “Show me the images of the Mediterranean Sea which include an algal bloom”. The possibility to retrieve a specific set of land images starting from a query expressed by a final user can quickly increase the interoperability and the diffusion of applications able to efficiently use EO data. In this work, we present a brief overview of the most successful application of this formalization strategy focusing on the tools and approaches for creating a robust and efficient domain geo-ontology. Furthermore, we describe the approach adopted to define the specific ontology used in the SEO-DWARF project, including the strategy adopted for implementing and populating it.
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Marco Polignano, Marco de Gemmis, Vasilis Kopsacheilis, Michail Vaitis, Jenny Malig, Dominik Grether, Ilias Ioannou, Anastasia Sarelli, Vito De Pasquale, Sergio Samarelli, Pol Kolokoussis, Kleanthis Karamvasis, Milto Miltiadou, Christiana Papoutsa, Olivier Regniers, Virginie Lafon, Konstantinos Topouzelis , and Bogdan Despotov "A semantic representation of EO data for image retrieval based on natural language queries", Proc. SPIE 10773, Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), 1077306 (6 August 2018); https://doi.org/10.1117/12.2325839
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KEYWORDS
Image retrieval
Satellites
Satellite imaging
Image processing
Water
Earth observing sensors
Ocean optics
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