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A data management technology using extended R-tree based on three dimension data

Jianlin Zhang

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Abstract

Managing large data is a critical problem for the geospatial collection. Extended r-tree introduced in this paper is used to connect spatial index and level of detail model for increasing data process effectiveness. Meanwhile, extended r-tree applied in database also greatly improves spatial index and level of detail model inquiry speed. Tests and results are provided in the paper to prove the effectiveness of extended r-tree applied in the system.

About this research paper

What this paper is about

Managing large data is a critical problem for the geospatial collection. Extended r-tree introduced in this paper is used to connect spatial index and level of detail model for increasing data process effectiveness. Meanwhile, extended r-tree applied in database also greatly improves spatial index and level of detail model inquiry speed. Tests and results are provided in the paper to prove the effectiveness of extended r-tree applied in the system.

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Available abstract

Managing large data is a critical problem for the geospatial collection. Extended r-tree introduced in this paper is used to connect spatial index and level of detail model for increasing data process effectiveness. Meanwhile, extended r-tree applied in database also greatly improves spatial index and level of detail model inquiry speed. Tests and results are provided in the paper to prove the effectiveness of extended r-tree applied in the system.

Key concepts: Geospatial analysis, R-tree, Computer science, Dimension (graph theory), Tree (set theory), Spatial database, Data mining, Index (typography)

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