Topological relations in the world of minimum bounding rectangles: a study with R-trees
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
On local heuristics to speed up polygon-polygon intersection tests
Proceedings of the 7th ACM international symposium on Advances in geographic information systems
Computational Geometry in C
Quadtree and R-tree indexes in oracle spatial: a comparison using GIS data
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
A Storage and Access Architecture for Efficient Query Processing in Spatial Database Systems
SSD '93 Proceedings of the Third International Symposium on Advances in Spatial Databases
Efficient Processing of Large Spatial Queries Using Interior Approximations
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Spatial indexing in microsoft SQL server 2008
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Topological relationship query processing for complex regions in Oracle Spatial
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Point-polygon topological relationship query using hierarchical indices
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Quick geo-fencing using trajectory partitioning and boundary simplification
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Geodetic distance queries on r-trees for indexing geographic data
SSTD'13 Proceedings of the 13th international conference on Advances in Spatial and Temporal Databases
| Hi-index | 0.00 |
As Global Positioning Systems (GPSs) are increasingly ubiquitous, spatial database systems are also encountering increasing use of location or point data, which is often expressed in geodetic coordinates: longitude and latitude. A simple but very important question regarding this data is whether the locations lie within a given region. This is normally called the point-inpolygon (PIP) problem. Within the Geodetic space, PIP queries have additional challenges that are not present in the Cartesian space. In this paper, we discuss several techniques implemented in Oracle Spatial to speed up geodetic PIP query processing. Our experiments utilizing real-world data sets demonstrate the PIP query performance can be significantly improved using these new techniques.