程昌秀. 矢量数据多尺度空间索引方法的研究[J]. 武汉大学学报 ( 信息科学版), 2009, 34(5): 597-601.
引用本文: 程昌秀. 矢量数据多尺度空间索引方法的研究[J]. 武汉大学学报 ( 信息科学版), 2009, 34(5): 597-601.
CHENG Changxiu. A Multi-scale Spatial Index Method[J]. Geomatics and Information Science of Wuhan University, 2009, 34(5): 597-601.
Citation: CHENG Changxiu. A Multi-scale Spatial Index Method[J]. Geomatics and Information Science of Wuhan University, 2009, 34(5): 597-601.

矢量数据多尺度空间索引方法的研究

A Multi-scale Spatial Index Method

  • 摘要: 阐述了近年来国内外出现的Reactive Tree、GAP-tree、Multi-Scale Hilbert R-tree、Multiple R-tree等6种矢量数据多尺度空间索引方法,对它们的优缺点作了较为详细的评述,为索引方法的选择和应用提供了一定的理论依据。最后,给出了对后续研究有指导性的结论,提出了高维索引、优化索引等多尺度空间索引方法未来的研究方向。

     

    Abstract: The problem about multi-representations of spatial data is one of the hot topics in modern GIS.We pointed out that all kinds of published solutions could be concluded as three kinds of type techniques: explicit storage of multi-scale vector data,multi-scale spatial index,multi-scale vector data storage structure.Because there is more fertile soil to seed multi-scale spatial index method,we expatiated six kinds of multi-scale spatial index method,such as Reactive Tree,GAP-tree,Multi-Scale Hilbert R-tree,Multiple R-tree,and followed their development in recent years.According to our research experiments,we discussed their advantages and disadvantages,and provided some academic bases for their chosen and applications.Finally,we drawn some conclusions to guide the research on multi-scale spatial methods,and proposed the further research on multi-dimension index and optimized index.

     

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