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Cited by 458

The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.

Towards a general theory of geographic representation in GIS

Open access
Goodchild, Michael F., Yuan, May, Cova, Thomas J.·2007·International Journal of Geographical Information Science

Abstract

Geographic representation has become more complex through time as researchers have added new concepts, leading to apparently endless proliferation and creating a need for simplification. We show that many of these concepts can be derived from a single foundation that we term the atomic form of geographic information. The familiar concepts of continuous fields and discrete objects can be derived under suitable rules applied to the properties and values of the atomic form. Fields and objects are further integrated through the concept of phase space, and in the form of field objects. A second atomic concept is introduced, termed the geo‐dipole, and shown to provide a foundation for object fields, metamaps, and the association classes of object‐oriented data modelling. Geographic dynamics are synthesized in a three‐dimensional space defined by static or dynamic object shape, the possibility of movement, and the possibility of dynamic internal structure. The atomic form also provides a tentative argument that discrete objects and continuous fields are the only possible bases for geographic representation.

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Metadata

Authors
Goodchild, M. F., Yuan, M., & Cova, T. J.
Venue
International Journal of Geographical Information Science
Published
2007-03
Volume
21
Issue
3
Pages
239-260
ISSN
  • 0269-3798 (ISSN-L)
  • 1365-8816
  • 1362-3087
OpenAlex
W1966470704
Cited by
458
References
43
FWCI
105.49
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Towards a general theory of geographic representation in GIS. https://app.cochat.ai/papers/10.1080/13658810600965271
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Goodchild, M. F., Yuan, M., & Cova, T. J. (2007). Towards a general theory of geographic representation in GIS. International Journal of Geographical Information Science. https://doi.org/10.1080/13658810600965271

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.