Efficient classification of billions of points into complex geographic regions using hierarchical triangular mesh

Dániel Kondor, László Dobos, I. Csabai, András Bodor, G. Vattay, Tamás Budavári, Alexander S. Szalay

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

We present a case study about the spatial indexing and regional classification of billions of geographic coordinates from geo-tagged social network data using Hierarchical TriangularMesh (HTM) implemented for Microsoft SQL Server. Due to the lack of certain features of the HTM library, we use it in conjunction with the GIS functions of SQL Server to significantly increase the efficiency of pre-filtering of spatial filter and join queries. For example, we implemented a new algorithm to compute the HTM tessellation of complex geographic regions and precomputed the intersections of HTM triangles and geographic regions for faster falsepositive filtering. With full control over the index structure, HTM-based pre-filtering of simple containment searches outperforms SQL Server spatial indices by a factor of ten and HTM-based spatial joins run about a hundred times faster.

Original languageEnglish
Title of host publicationACM International Conference Proceeding Series
PublisherAssociation for Computing Machinery
ISBN (Print)9781450327220
DOIs
Publication statusPublished - 2014
Event26th International Conference on Scientific and Statistical Database Management, SSDBM 2014 - Aalborg, Denmark
Duration: Jun 30 2014Jul 2 2014

Other

Other26th International Conference on Scientific and Statistical Database Management, SSDBM 2014
CountryDenmark
CityAalborg
Period6/30/147/2/14

Fingerprint

Servers
Geographic information systems

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Kondor, D., Dobos, L., Csabai, I., Bodor, A., Vattay, G., Budavári, T., & Szalay, A. S. (2014). Efficient classification of billions of points into complex geographic regions using hierarchical triangular mesh. In ACM International Conference Proceeding Series [4] Association for Computing Machinery. https://doi.org/10.1145/2618243.2618245

Efficient classification of billions of points into complex geographic regions using hierarchical triangular mesh. / Kondor, Dániel; Dobos, László; Csabai, I.; Bodor, András; Vattay, G.; Budavári, Tamás; Szalay, Alexander S.

ACM International Conference Proceeding Series. Association for Computing Machinery, 2014. 4.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kondor, D, Dobos, L, Csabai, I, Bodor, A, Vattay, G, Budavári, T & Szalay, AS 2014, Efficient classification of billions of points into complex geographic regions using hierarchical triangular mesh. in ACM International Conference Proceeding Series., 4, Association for Computing Machinery, 26th International Conference on Scientific and Statistical Database Management, SSDBM 2014, Aalborg, Denmark, 6/30/14. https://doi.org/10.1145/2618243.2618245
Kondor D, Dobos L, Csabai I, Bodor A, Vattay G, Budavári T et al. Efficient classification of billions of points into complex geographic regions using hierarchical triangular mesh. In ACM International Conference Proceeding Series. Association for Computing Machinery. 2014. 4 https://doi.org/10.1145/2618243.2618245
Kondor, Dániel ; Dobos, László ; Csabai, I. ; Bodor, András ; Vattay, G. ; Budavári, Tamás ; Szalay, Alexander S. / Efficient classification of billions of points into complex geographic regions using hierarchical triangular mesh. ACM International Conference Proceeding Series. Association for Computing Machinery, 2014.
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