Vector data reading method and system, vector data visualization method and system

Abstract

The invention relates to the technical field of vector data reading and visualization, in particular to a vector data reading method and system, and a vector data visualization method and system. The reading method comprises the following steps that: according to a minimum pixel displayed on a screen, calculating a logic size corresponding to data inquired under different display proportional scales to obtain data which is displayed in a display range which needs to be read in a spatial database; traversing each simple element of the obtained data, and establishing a cache; and establishing an intersectant grid index for the established data. By use of the vector data reading method and system and the vector data visualization method and system, the data is filtered to effectively reduce a data reading amount, and initial caching data is created in a memory database in a deployment environment to improve a query hit rate and reduce the pulling of server data.

Description

technical field [0001] The invention relates to the technical field of vector data reading and visualization, in particular to a vector data reading method, a vector data reading system, a vector data fast visualization method and a vector data fast visualization system. Background technique [0002] Vector data is one of the important information for GIS storage, expression and management. It is spatial data stored and represented by vector data structure. By recording coordinates, basic elements such as points, lines, and planes are used to represent various geographic spatial entities. The coordinate space represented by it is continuous, so any position, length, area, etc. of geographic entities can be precisely defined. Vector data is generally obtained automatically / semi-automatically by measurement methods or created by manual input. Users can analyze and modify it, and it is an important information resource for various in-depth research work. [0003] With the larg...

AI Technical Summary

Problems solved by technology

In the process of using this visualization method, when the data is stored locally, it will be limited by the local storage capacity; and when the data is stored on the server, it will take a long time to transfer the data back to the local when drawing

Therefore, for large-scale data, fast visualization cannot be achieved

[0006] Most of the traditional data caching schemes rely on the local file system. This caching method will improve the data processing speed in common environments, but when a large number of users access concurrently or the data table grows massively, this caching method will become the bottleneck of the system. There are difficulties in sharing and scalability

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