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The Zones Algorithm for Finding Points-Near-a-Point or Cross-Matching Spatial Datasets
Zones index an N-dimensional Euclidian or metric space to efficiently support
points-near-a-point queries either within a dataset or between two datasets.
The approach uses relational algebra and the B-Tree mechanism found in almost
all relational database systems. Hence, the Zones Algorithm gives a
portable-relational implementation of points-near-point, spatial cross-match,
and self-match queries. This article corrects some mistakes in an earlier
article we wrote on the Zones Algorithm and describes some algorithmic
improvements. The Appendix includes an implementation of point-near-point,
self-match, and cross-match using the USGS city and stream gauge database