Due to the increasing popularity of spatial databases, researchers have focused their efforts on improving the query processing performance of the most expensive spatial database ...
Yun-Wu Huang, Matthew C. Jones, Elke A. Rundenstei...
The spatial join operation is benchmarked using variants of well-known spatial data structures such as the R-tree, R-tree, R+-tree, and the PMR quadtree. The focus is on a spatia...
Spatial indexes, such as the PMR quadtree, are important in spatial databases for efficient execution of queries involving spatial constraints, especially when the queries involve...
One of the most important operations in spatial access needed systems are spatial joins. Using for processing such operations R-tree like structures is intensively studies now. Th...
Spatial join is an important yet costly operation in spatial databases. In order to speed up the execution of a spatial join, the input tables are often indexed based on their spa...
Spatial joins are one of the most important operations for combining spatial objects of several relations. In this paper, spatial join processing is studied in detail for extended...
Thomas Brinkhoff, Hans-Peter Kriegel, Ralf Schneid...
The basic concept for processing spatial joins consists of two steps: First, the spatial join is performed on the minimum bounding rectangles of the objects by using a spatial acce...
We discovered a surprising law governing the spatial join selectivity across two sets of points. An example of such a spatial join is "find the libraries that are within 10 m...
Christos Faloutsos, Bernhard Seeger, Agma J. M. Tr...
The most costly spatial operation in spatial databases is a spatial join with combines objects from two data sets based on spatial predicates. Even if the execution time of sequen...