Ontology-based semantic classification of satellite images: Case of major disasters

Bouyerbou, Hafidha, Bechkoum, Kamal ORCID: 0000-0001-5857-2763, Benblidia, Nadjia and Lepage, Richard (2014) Ontology-based semantic classification of satellite images: Case of major disasters. In: IEEE International Geoscience and Remote Sensing Symposium (IGARSS), JUL 13-18, 2014, Quebec, CANADA.

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The International Charter 'Space and Major Disasters' is regularly activated during a catastrophic event and offers rescue teams comprehensive damage maps. Most of these maps are built by means of satellite image manual processing, which is often complex and demanding in terms of time and energy. Automatic processing supplies prompt treatment. Nevertheless, it usually presents a semantic gap handicap. The exploitation of ontologies to bridge the semantic gap has been widely recommended due to their quality of knowledge representation, expression, and discovery. In this work, we present an ontology-based semantic hierarchical classification method to undertake this problem. Ontology components are translated to image-based parameters and exploited to assist the classification process at two levels, and using 12 classes. The region of interest is selected from the first level and exhaustively analyzed and classified at the second level. The 2010 Haiti earthquake was selected as study area for this work. Experiments were performed using very high resolution multi-temporal QuickBird imagery and eCognition software.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Major disaster, semantics, ontology, satellite image, classification.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Schools and Research Institutes > School of Business, Computing and Social Sciences
Research Priority Areas: Applied Business & Technology
Depositing User: Susan Turner
Date Deposited: 08 Dec 2015 14:56
Last Modified: 31 Aug 2023 08:01
URI: https://eprints.glos.ac.uk/id/eprint/2891

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