Affiliation:
1. University of Florida, Gainesville, FL
2. FernUniversität Hagen, Hagen, Germany
Abstract
For a long time topological relationships between spatial objects have been a focus of research in a number of disciplines like artificial intelligence, cognitive science, linguistics, robotics, and spatial reasoning. Especially as predicates they support the design of suitable query languages for spatial data retrieval and analysis in spatial databases and geographical information systems (GIS). Unfortunately, they have so far only been defined for and applicable to simplified abstractions of spatial objects like single points, continuous lines, and simple regions. With the introduction of
complex spatial data types
an issue arises regarding the design, definition, and number of topological relationships operating on these complex types. This article closes this gap and first introduces definitions of general and versatile spatial data types for
complex points
,
complex lines
, and
complex regions
. Based on the well known 9-intersection model, it then determines the complete sets of mutually exclusive topological relationships for all type combinations. Completeness and mutual exclusion are shown by a proof technique called
proof-by-constraint-and-drawing
. Due to the resulting large numbers of predicates and the difficulty of handling them, the user is provided with the concepts of
topological cluster predicates
and
topological predicate groups
, which permit one to reduce the number of predicates to be dealt with in a user-defined and/or application-specific manner.
Publisher
Association for Computing Machinery (ACM)
Cited by
145 articles.
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