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Proceedings Paper

Study of seamless organization and storage structure for massive spatio-temporal data
Author(s): Jiong Xie; Renyi Liu; Nan Liu
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Paper Abstract

Integrative management of massive spatio-temporal data and the relevant capabilities for time series analysis are important research targets of new generation GIS software architecture. At present, solid developments are imperatively needed in technology for effective organization and storage of massive spatio-temporal data. Oriented to spatio-temporal multi-dimension structure, a massive spatio-temporal data seamless organization and storage model based on spatio-temporal partition (STP), spaito-temporal clustering (STC) is presented, and the test on single table of 2GB to 60 GB shows that integration of STP and STC can improve performance of spaito-temporal search effectively.

Paper Details

Date Published: 2 December 2005
PDF: 9 pages
Proc. SPIE 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications, 60451T (2 December 2005); doi: 10.1117/12.651254
Show Author Affiliations
Jiong Xie, Zhejiang Univ. (China)
Renyi Liu, Zhejiang Univ. (China)
Nan Liu, Zhejiang Univ. (China)

Published in SPIE Proceedings Vol. 6045:
MIPPR 2005: Geospatial Information, Data Mining, and Applications
Jianya Gong; Qing Zhu; Yaolin Liu; Shuliang Wang, Editor(s)

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