International Journal of Geographical Information Science
(2005) 19(10): 1039-1056.
A Combinatorial Data Model for Representing
Topological Relations among 3D Geographic Features
in Micro-spatial Environments
Jiyeong Lee and Mei-Po Kwan
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 geographic 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 modeled 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.
Key Words: 3D GIS, Topological Data Model, Poincaré Duality,
Combinatorial Data Model
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