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15 October 2009 Spatial index study for multi-dimension vector data based on improved quad-tree encoding
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Proceedings Volume 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining; 749235 (2009) https://doi.org/10.1117/12.837968
Event: International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, 2009, Wuhan, China
Abstract
Now the geographic information system obtains the widespread application in various fields. These small geographic application systems, covering small regions, may manage large or medium scale data, but on the other hand in regard to the large geographic information systems, managing entire national territory geography information, basically take the small scale data as a foundation. Those system final users not only need to establish the corresponding application in the entire country or the global spatial data, but they often even more pay more attention to some local data or the details. Therefore it needs to establish an efficient spatial index for these multi-dimension vector data in the large geographic information systems. This article introduced a method to improve quad-tree encoding. It is a kind of multi-encoding system for multi-dimension vector data. It can provide variable resolution ability and make neighboring inquiry directly. The method proved to have high level efficiency in organization of different origin, different projection and different scale vector data. It accomplished an integrated information combination between large scale, high resolution maps (mostly focus on cities) and small scale, wide scope maps including national or international data.
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Yuxiang Li and Hong Wang "Spatial index study for multi-dimension vector data based on improved quad-tree encoding", Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 749235 (15 October 2009); https://doi.org/10.1117/12.837968
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