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Modélisation spatio-temporelle multi-niveau à base d'ontologies pour le suivi de la dynamique en imagerie satellitaire

Abstract : Modeling the dynamics of spatio-temporal objects is part of the research subjects for monitoring and interpretation of the changes affecting the Earth. Satellite images are an effective way for studying the dynamics of spatio-temporal phenomena, including urbanization, deforestation, flooding, desertification, and so on, that can occur on the surface of the Earth. Various models and approaches have been proposed to model the evolution of the spatio-temporal objects. However, each of these models has a limited ability to capture the evolution of the different characteristics of the environment, and the representation structure used by each model does not fully capture the semantics of the evolution of a spatio-temporal object. The works of our thesis interested in modeling the dynamics of spatio-temporal objects for changes interpretation in satellite imagery. Therefore, we proposed initially a multi-level ontological architecture for representation and modeling the dynamic of spatio-temporal objects and process. Also, we have presented a new semantic scene interpretation strategy for change interpretation in remote sensing imagery. The application Framework concerns the semantic interpretation of a satellite images scenes for change interpretation of phenomena, such as urbanization and deforestation. The result is a change map that can guide better management of the land use/cover.
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Submitted on : Tuesday, March 12, 2019 - 10:23:08 AM
Last modification on : Friday, October 23, 2020 - 4:40:06 PM
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  • HAL Id : tel-02064710, version 1


Fethi Ghazouani. Modélisation spatio-temporelle multi-niveau à base d'ontologies pour le suivi de la dynamique en imagerie satellitaire. Intelligence artificielle [cs.AI]. Ecole nationale supérieure Mines-Télécom Atlantique; Ecole Nationale des Sciences Informatiques (Tunis), 2018. Français. ⟨NNT : 2018IMTA0122⟩. ⟨tel-02064710⟩



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