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The Zones Algorithm for Finding Points-Near-a-Point or Cross-Matching Spatial Datasets

Jim Gray·Maria A. Nieto-Santisteban·Alexander S. Szalay
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Abstract

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.

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Jim Gray, Maria A. Nieto-Santisteban, Alexander S. Szalay. 2007-01-26. The Zones Algorithm for Finding Points-Near-a-Point or Cross-Matching Spatial Datasets. https://arxiv.org/abs/cs/0701171

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