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Spatio-temporal big data grid coding efficient visualization method and system

A space-time data and grid coding technology, which is applied in database indexing, structured data retrieval, geographic information database, etc., can solve the problems of low efficiency of space-time big data visualization, large visualization time consumption, and large data request volume, etc., to improve Data request and data query efficiency, improve query efficiency and visual expression, and reduce response time

Active Publication Date: 2020-10-16
CHINA UNIV OF MINING & TECH (BEIJING)
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the large amount of spatio-temporal big data and various acquisition methods, the amount of data requests on the Web side when acquiring back-end data is very large, resulting in a long time for data query, as well as time for data analysis and processing, and the time for visualization The consumption is also large, which leads to inefficiency in the visualization of the entire spatiotemporal big data

Method used

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  • Spatio-temporal big data grid coding efficient visualization method and system
  • Spatio-temporal big data grid coding efficient visualization method and system
  • Spatio-temporal big data grid coding efficient visualization method and system

Examples

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Embodiment 1

[0053] An efficient visualization method for spatial-temporal big data grid coding, the method comprising the following steps:

[0054] A. Establish a spatio-temporal big data visualization model, construct a grid-coded index data structure on the spatio-temporal big data visualization model, and obtain a coded index data set, and store the coded index data set in the spatio-temporal database. The coded index data set includes codes , The corresponding relationship between index and data; select or set the visual domain on the spatio-temporal big data visualization model, and obtain the visual domain coding index data set corresponding to the visual domain;

[0055] B. Set the visualization main thread and data request sub-thread for the visual domain of the spatio-temporal big data visualization model; collect spatio-temporal data and perform grid coding dimension reduction projection processing and transmit it to the data request sub-thread, and the data request sub-thread is...

Embodiment 2

[0075] An efficient visualization method for spatial-temporal big data grid coding, the method comprising the following steps:

[0076] A. Establish a spatio-temporal big data visualization model, construct a grid coded index data structure on the spatio-temporal big data visualization model, the construction method of the grid coded index data structure is as follows: according to the principle of equal longitude and latitude The visualization model is divided into several sub-level grid units according to the quadtree grid;

[0077] According to the difference l in gridding 0 , latitude difference b 0 , the difference l in the meshing of the visible domain 1 , latitude difference b 1 , to obtain the sets X and Y of the row and column numbers of the visual field encoding:

[0078] Visibility encoding line number set

[0079] A collection of column numbers for viewport encodings Where x represents the grid coding level;

[0080] According to the Morton coding rules, ...

Embodiment 3

[0085] Such as figure 1 As shown, an efficient visualization method for spatial-temporal big data grid coding, the method includes the following:

[0086] S1. Establish a spatio-temporal big data visualization model, build a quadtree grid coding index in a local area on the spatio-temporal big data visualization model, perform grid coding and dimensionality reduction expression on the spatio-temporal big data, and realize the integration of "coding-index-data", Obtain the geospatial encoding set (also known as the encoding index data set) corresponding to the view domain;

[0087] S2. Propose a method for separating front-end data requests and visualization threads of gridded spatio-temporal big data. Sub-threads (also known as data request sub-threads) perform gridded spatio-temporal data queries based on the geospatial code set of the visual domain, and then communicate through threads Pass the query results to the main thread (also known as the visualization main thread), ...

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Abstract

The invention discloses a spatio-temporal big data grid coding efficient visualization method and system. The system comprises a spatio-temporal big data visualization model, a spatio-temporal database, an acquisition module, a grid coding module and a visual domain data visualization processing module. A grid coding index data structure is constructed on the spatio-temporal big data visualizationmodel, a visual domain selection module is arranged on the spatio-temporal big data visualization model, and the visual domain data visualization processing module comprises a visualization main thread module and a data request sub-thread module. According to the invention, a visual domain can be selected or set on the spatio-temporal big data visualization model according to needs, and the datarequest sub-thread queries spatio-temporal data corresponding to the visual domain according to a visual domain coding index data set and transmits the spatio-temporal data to the visualization main thread for visual expression. The method and the system have the advantages of data query, visual expression, high visual loading quality and efficiency and the like, and the fluency of data loading and visualization is remarkably improved.

Description

technical field [0001] The invention relates to the technical field of spatiotemporal big data visualization, in particular to a method and system for efficient visualization of spatiotemporal big data grid coding. Background technique [0002] Spatio-temporal big data is based on a unified spatio-temporal benchmark, and activities in space-time are directly or indirectly associated with locations. It is the "summation" of the data sets of the quantity and quality characteristics of each element (phenomenon) of the spatial structure and spatial relationship of the real geographical world, including human activities, and its changes in time and space, with space, time, attributes, multi-source ( Meta) heterogeneous, multi-dimensional dynamic and other characteristics. Web-side visualization of spatio-temporal big data usually requires the front-end browser to send data requests, the back-end server receives the front-end requests for data query and data processing, and then ...

Claims

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Application Information

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IPC IPC(8): G06F16/29G06F16/22
CPCG06F16/2246G06F16/29
Inventor 李军孙文童刘举庆梅晓龙
Owner CHINA UNIV OF MINING & TECH (BEIJING)
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