Spatial relations are becoming an important aspect of spatial access methods because of the increasing interest on qualitative spatial information processing. In this paper we show how queries involving spatial relations can be transformed to range queries and implemented in existing DBMSs. We provide a performance analysis of B- and R- tree indexing methods to support such queries and we evaluate the analytical formulas using experimental results. The proposed analytical models for the expected retrieval cost of spatial relations are proved to be good guidelines for a spatial query optimiser.

The authors examined whether absolute and relative judgments about global-scale locations and distances were generated from common representations. At the end of a 10-week class on the regional geography of the United States, participants estimated the latitudes of 16 North American cities and all possible pairwise distances between them. Although participants were relative experts, their latitude estimates revealed the presence of psychologically based regions with large gaps between them and a tendency to stretch North America southward toward the equator. The distance estimates revealed the same properties in the representation recovered via multidimensional scaling. Though the aggregated within- and between-regions distance estimates were fitted by Stevens’s law (S. S. Stevens, 1957), this was an averaging artifact: The appropriateness of a power function to describe distance estimates depended on the regional membership of the cities. The authors conclude that plausible reasoning strategies, combined with regionalized representations and beliefs about the location of these relative to global landmarks, underlie global-scale latitude and distance judgments.