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A Hybrid Spatio-Temporal Data Model and Structure (HST-DMS) for Efficient Storage and Retrieval of Land Use Information

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Abstract

While the incorporation of geographical and environmental modeling with GIS requires software support for storage and retrieval of spatial information that changes over time, it continues to be an unresolved issue with modern GIS software. Two complementary approaches have been used to manage the spatial and temporal heterogeneity within datasets that use a field-based representation of the world. Some researchers have proposed new data models that partition space into discrete elements on an as-needed basis following each temporal event, while others have focused on eliminating duplication of repeated data elements present in spatio-temporal information. It is proposed in this paper that both approaches have merit and can be combined to create a Hybrid Spatio-Temporal Data Model and Structure (HST-DMS) that efficiently supports spatio-temporal data storage and querying. Specifically, Peuquet and Duan's (1995) Event-based Spatio-Temporal Data Model (ESTDM) and the Overlapping R-tree (Guttman 1984, Tzourmanis et al. 2000) are utilized to create a prototype used to store information about urban expansion for the town of Carbondale, Illinois.
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Document Type: Research Article

Affiliations: 1: Department of Geography McGill University 2: School of Computer Science University of Nevada at Las Vegas

Publication date: June 1, 2004

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