A combinatorial data model for representing topological relations among 3D geographical features in micro-spatial environments

J. Lee, M. P. Kwan

Research output: Contribution to journalArticlepeer-review

106 Scopus citations

Abstract

This research is motivated by the need for 3D GIS data models that allow for 3D spatial query, analysis and visualization of the subunits and internal network structure of 'micro-spatial environments' (the 3D spatial structure within buildings). It explores a new way of representing the topological relationships among 3D geographical features such as buildings and their internal partitions or subunits. The 3D topological data model is called the combinatorial data model (CDM). It is a logical data model that simplifies and abstracts the complex topological relationships among 3D features through a hierarchical network structure called the node-relation structure (NRS). This logical network structure is abstracted by using the property of Poincaré duality. It is modelled and presented in the paper using graph-theoretic formalisms. The model was implemented with real data for evaluating its effectiveness for performing 3D spatial queries and visualization.

Original languageEnglish
Pages (from-to)1039-1056
Number of pages18
JournalInternational Journal of Geographical Information Science
Volume19
Issue number10
DOIs
StatePublished - Nov 2005

Keywords

  • 3D GIS
  • Combinatorial data model
  • Poincaré duality
  • Topological data model

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