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QR-tree:An Efficient Spatial Indexing Structure for GIS with Very Large Spatial Database

Guo Jing

Open publisher page 3 citations

Abstract

Spatial indexing techniques can efficiently improve the storage and query efficiency. IN the large spatial database of GIS, the traditional spatial indexing structures, the R-tree has the problem that with the growing dimensionality and data number, the searching function will decrease greatly. On the basis of the analysis of R-tree, this paper puts forward a new spatial indexing structure for GIS with very large spatial database-the QR-tree.

About this research paper

What this paper is about

Spatial indexing techniques can efficiently improve the storage and query efficiency. IN the large spatial database of GIS, the traditional spatial indexing structures, the R-tree has the problem that with the growing dimensionality and data number, the searching function will decrease greatly. On the basis of the analysis of R-tree, this paper puts forward a new spatial indexing structure for GIS with very large spatial database-the QR-tree.

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Spatial indexing techniques can efficiently improve the storage and query efficiency. IN the large spatial database of GIS, the traditional spatial indexing structures, the R-tree has the problem that with the growing dimensionality and data number, the searching function will decrease greatly. On the basis of the analysis of R-tree, this paper puts forward a new spatial indexing structure for GIS with very large spatial database-the QR-tree.

Key concepts: Search engine indexing, Spatial database, R-tree, Computer science, Spatial analysis, Database, Spatial query, Curse of dimensionality

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