Spatial data indexing method integrating GeoHash and Quadtree

Abstract

The invention provides a spatial data indexing method integrating GeoHash and Quadtree. The method comprises the steps of creating an improved quadtree index structure and dynamically updating from bottom to top ,wherein the improved quadtree index structure comprises an improved quadtree, a direct access table and a Hash index table established on a space object, the improved quadtree adopts a region division rule based on GeoHash and quadtree similarity, a space region is divided according to the GeoHash, the quadtree with nodes in one-to-one correspondence with GeoHash codes is establishedaccording to a grid, and a direct access table is used for pointing to all intermediate nodes in the improved quadtree; and a corresponding space object record in the improved quadtree leaf child nodeis accessed by using a Hash index table based on a space object identifier based on a bottom-up dynamic updating algorithm, and when the space object sends a position updating request, a plurality ofupdating strategies are adopted according to the position change degree of the space object. According to an improved quadtree index structure, an extended bottom-up dynamic updating algorithm is provided, and frequent updating operation of indexes is supported.

Description

technical field [0001] The invention relates to the technical field of spatial data indexing, in particular to a spatial data indexing method integrating GeoHash and Quadtree. Background technique [0002] Against the backdrop of the rapid development of technologies such as the Internet and GNSS (Global Navigation Satellite System) positioning, the types, scale, and speed of spatial data are increasing rapidly. Massive spatial data must contain a lot of useful information, management and retrieval. These massive spatial data often require a large number of update operations. How to manage these massive spatial data and provide an efficient indexing mechanism for frequently updated massive data is a key problem that needs to be solved urgently. [0003] At present, scholars at home and abroad have proposed many spatial data storage and retrieval methods for this problem, such as the Quad-Tree Index that can continuously divide the spatial range into four equal parts to impro...

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Problems solved by technology

[0004] For the inherent top-down update mode of the existing index structure, the necessary index page disk I / O is required to access the data page where the spatial object is located. If it is used to manage massive and frequently updated spatial data, the index structure will be violent. changes, resulting in a large I / O cost, and the characteristics of being difficult to support concurrent updates, so in many applications its dynamic update performance often cannot meet the technical problems of actual needs. The present invention provides a spatial data index integrating GeoHash and Quadtree method

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