SHG-Tree: an efficient granularity-based spatial index structure

Yintian Liu; Yingming Liu; Kaikuo Xu; Tao Zeng; Jiaoling Zheng

doi:10.1117/12.813093

10 November 2008 SHG-Tree: an efficient granularity-based spatial index structure

Yintian Liu, Yingming Liu, Kaikuo Xu, Tao Zeng, Jiaoling Zheng

Proceedings Volume 7146, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses; 714603 (2008) https://doi.org/10.1117/12.813093
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

Abstract

To improve the access efficiency of multidimensional spatial database, this study proposes a new index structure named Space Hypercube Grid Tree (SHG-Tree). By avoiding the problems of node split and recombination, SHG-Tree can efficiently support the common operations over spatial database containing objects with dynamic region. The main contributions of this paper include: (1) Proposes SHG-Tree of n-dimensional space with a hierarchical tree structure. It reflects the region overlapping relationship of hypercube grid units with different granularity. (2) Proposes the linearization methods to present the bounding rectangle of object as a union of variant granularity hypercube grids. (3) Gives operations of SHG-Tree. Experiments result shows the size of SHG-Tree is small enough to remain in main memory even to very large spatial database by applying proper linearization strategy and the queries on SHG-Tree are less than ten milliseconds to ensure the real-time of query.

Citation Download Citation

Yintian Liu, Yingming Liu, Kaikuo Xu, Tao Zeng, and Jiaoling Zheng "SHG-Tree: an efficient granularity-based spatial index structure", Proc. SPIE 7146, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses, 714603 (10 November 2008); https://doi.org/10.1117/12.813093

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KEYWORDS

Databases

Data modeling

Geographic information systems

Radon

Detection and tracking algorithms

Image segmentation

Information technology

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