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A hybrid data model for dynamic GIS: application to marine geomorphological dynamics

Authors :
Younes Hamdani
Rémy Thibaud
Christophe Claramunt
Institut de Recherche de l'Ecole Navale (IRENAV)
Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Arts et Métiers Sciences et Technologies
HESAM Université (HESAM)-HESAM Université (HESAM)
École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)
Source :
International Journal of Geographical Information Science, International Journal of Geographical Information Science, Taylor & Francis, 2020, pp.1-25. ⟨10.1080/13658816.2020.1829628⟩
Publication Year :
2020
Publisher :
HAL CCSD, 2020.

Abstract

International audience; The search for the most appropriate GIS data model to integrate, manipulate and analyse spatio-temporal data raises several research questions about the conceptualisation of geographic spaces. Although there is now a general consensus that many environmental phenomena require field and object conceptualisations to provide a comprehensive GIS representation, there is still a need for better integration of these dual representations of space within a formal spatio-temporal database. The research presented in this paper introduces a hybrid and formal dual data model for the representation of spatio-temporal data. The whole approach has been fully implemented in PostgreSQL and its spatial extension PostGIS, where the SQL language is extended by a series of data type constructions and manipulation functions to support hybrid queries. The potential of the approach is illustrated by an application to underwater geomorphological dynamics oriented towards the monitoring of the evolution of seabed changes. A series of performance and scalability experiments are also reported to demonstrate the computational performance of the model.

Details

Language :
English
ISSN :
13658816 and 13658824
Database :
OpenAIRE
Journal :
International Journal of Geographical Information Science, International Journal of Geographical Information Science, Taylor & Francis, 2020, pp.1-25. ⟨10.1080/13658816.2020.1829628⟩
Accession number :
edsair.doi.dedup.....41940f71de2767a560f1eee05d17fba5
Full Text :
https://doi.org/10.1080/13658816.2020.1829628⟩