A trajectory data space-time density analysis system and an analysis method thereof

Abstract

The invention discloses a track data space-time density analysis system and an analysis method thereof. The technical scheme is as follows: the space-time density analysis module performs calculationby using target track data obtained by the track data preprocessing module to obtain space-time density values of track points, and the space-time distribution density visualization module draws the target track data and the space-time density values of the track points into a track scatter diagram and a space-time density curve respectively and presents the track scatter diagram and the space-time density curve to a user; And a result extraction module is used for extracting and storing a density analysis result which the user is interested in, and finally labeling at a corresponding positionon the map according to the latitude and longitude and the time information of the extraction result. The system and the method can serve wider application, the calculation process and result presentation are more visual, a user does not need to carry out excessive preprocessing on the data in advance, and the system is simpler to operate.

Description

technical field [0001] The invention discloses a trajectory data space-time density analysis system and an analysis method thereof, belonging to the technical field of trajectory data mining. Background technique [0002] Trajectory data mining is the process of discovering valuable information or knowledge contained in spatio-temporal trajectory data using relevant technologies and methods of data mining. The rapid development of communication technology has allowed people to obtain a large amount of trajectory data. How to effectively use this batch of data, analyze and mine valuable knowledge or patterns has attracted more and more attention. [0003] Most of the density analysis methods in trajectory data mining are developed on the basis of traditional spatial data mining. These spatial data processing methods have certain limitations in processing spatiotemporal trajectory data, and the application range of these methods is single. , mainly for specific clustering tas...

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Problems solved by technology

[0003]Most density analysis methods in trajectory data mining are developed on the basis of traditional spatial data mining. There are certain limitations when using trajectory data, and these methods have a single application range, mainly for specific clustering tasks

At present, there is a lack of in-depth research systems for trajectory data. How to uniformly analyze the spatiotemporal distribution characteristics of trajectory data and present the analysis results to users in a visualized form, so that users can use the spatiotemporal density analysis results , to further carry out in-depth research on trajectory data, for example, research on stop point extraction, position detection, noise discovery and elimination, semantic analysis of moving trajectory, etc., is an urgent direction to be solved

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