Design of an extended qualitative cardinal direction relation model based on ontology

Han Cao; Xin Wang; Jun Chen

doi:10.1117/12.813114

10 November 2008 Design of an extended qualitative cardinal direction relation model based on ontology

Han Cao, Xin Wang, Jun Chen

Proceedings Volume 7146, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses; 71460N (2008) https://doi.org/10.1117/12.813114
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

Abstract

Cardinal direction relation is an important spatial relation to determine directions and locations between spatial objects. Since 1987, some corn-based and projection-based direction relation models have been proposed. However, these existing models use different terms and methods to describe and represent direction relation, so it is difficult to share information in application systems. In order to support cardinal direction relation representing and reasoning according to explicit different level of details and improve the information reusing and interoperability, it is necessary to have explicit formalizations of mental concepts that people have about it. In this paper, we use ontology to set up a higher level of abstraction where the more valuable information about the meaning of the direction relation can be handled, and propose an extended qualitative description and reasoning cardinal direction model, which precisely describes cardinal direction relations between objects by separating the reference objects as point, line and area. This model has been implemented based on geo-ontology, and it can support common direction relation applications in spatial reasoning domain.

Citation Download Citation

Han Cao, Xin Wang, and Jun Chen "Design of an extended qualitative cardinal direction relation model based on ontology", Proc. SPIE 7146, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses, 71460N (10 November 2008); https://doi.org/10.1117/12.813114

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