Area query processing method and device for large-scale vector map data

Abstract

The embodiment of the invention discloses an area query processing method and device for the large-scale vector map data. The method comprises the following steps of dividing, stacking and analyzing amulti-stage vector map data layer and a natural condition attribute to form a composite data layer; calculating the area of each pattern spot of the composite data layer; constructing a gridding datalayer surface comprising a plurality of grid units on the basis of the gridding data layer surface; calculating a summary area of each natural condition attribute of a plurality of stages of land types in the gridding data level; gathering the gridding data level by level to form a pyramid type grid level; calculating the attribute area of each grid unit in the grid level corresponding to the query processing precision in the query processing range to form a query processing range attribute area list; and outputting a result of summarizing the areas in the list according to the query processing constraint condition. According to the grid hierarchy with controllable pyramid type query processing precision, the grid hierarchy corresponding to the query processing precision is selected, so that the query processing efficiency can be greatly improved, and various query processing requirements can be better met.

Description

technical field [0001] The invention relates to the field of vector map data query processing, in particular to an area query processing method and device for large-scale vector map data. Background technique [0002] Geographic Information System (GIS) is more and more widely used in various fields, and map data stored in vector form is gradually becoming a massive and refined data product that can be used for basic applications and production services. [0003] Vector map data query processing service is a comprehensive application field, which needs to associate multi-temporal and multi-type vector data materials with data processing algorithms, and then provide users with information publishing and online computing services through WEB services. Most of the mainstream commercial and open source software platforms provide technical support for data publishing services, but for the online area query and processing services that cannot be realized for large-scale vector map...

AI Technical Summary

Problems solved by technology

[0005] Query processing accuracy and query processing time are often difficult to balance

Providing online query processing services will inevitably face high time-consuming costs. Clients can only submit query processing tasks and wait for a long time, and the waiting time depends entirely on the size of the spatial query processing range.

In fact, most online query processing tasks do not require high query processing accuracy, and rough estimation results can meet the auxiliary decision-making requirements of spatial planning, but the uncontrollable query processing accuracy will lead to long query processing time, query processing The efficiency is correspondingly reduced, which cannot meet the needs of fast query processing

[0006] (2) Lack of rapid calculation and summary technology for the area of ​​land types in the custom query processing range

The problem with this method is that both boundary map cropping and complex map area calculation are too time-consuming, which is not conducive to fast statistical analysis services. Efficiency is not improved as it should be

As a large-scale vector map data information closely related to living space, it is of great value to use it to assist daily life and assist decision-making capabilities. Therefore, the online query and processing capabilities of data in the related existing technologies need to be further improved

[0008] In addition, there are fewer types of corresponding query processing constraints in the existing technology, which cannot well meet the user's large-scale and high-precision custom query processing needs

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