Abstract
The shape complexity of two-dimensional (2D) polygonal spatial objects has implications for how the object can be best represented in a spatial database, and for the query-processing performance of that object. Nevertheless few useful definitions of query-processing relevant spatial complexity are available. A query-processing oriented shape complexity measure is likely to be different from a fractal measure of shape complexity that focused on compression/decompression or a shape complexity measure that would be used for pattern recognition, and should give better performance for the analysis of query processing. It could be used to classify spatial objects, cluster spatial objects in multiprocessor database systems. In a recent paper Brinkhoff et al. (T. Brinkhoff, H-P. Kriegel, R. Shneider, A. Braun, Measuring the complexity of spatial objects, Proceedings of the 3rd ACM International Workshop on Advances in Geographic Information Systems, Baltimore, MD, 1995, pp. 109–117) demonstrated the usefulness of a spatial complexity measure. They did not, however, offer much theoretical justification for their choice of parameters nor for the functional form that they used. In this paper we present a conceptual framework for discussing the query processing oriented shape complexity measures for spatial objects. It is hoped that this will lead to the development of improved measures of spatial complexity.
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