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A hybrid data model for dynamic GIS: application to marine geomorphological dynamics
- 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.
- Subjects :
- Computer science
Geography, Planning and Development
0211 other engineering and technologies
0507 social and economic geography
Field
02 engineering and technology
Library and Information Sciences
computer.software_genre
Object
14. Life underwater
Hybrid data model
Marine geomorphology
Dynamic GIS
Hybrid data
021101 geological & geomatics engineering
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere
05 social sciences
Object (computer science)
Field (geography)
Data model
Dynamics (music)
Research questions
Data mining
050703 geography
computer
Information Systems
Subjects
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⟩