Massive trajectory point data visualization analysis method and medium

Abstract

The application discloses a large-scale trajectory point position data visual analysis method and medium, relates to the map trajectory visualization technical field, and the method comprises the following steps: S1, acquires the point position data set, draws the point position data set to the virtual plane according to the latitude and longitude, obtains the trajectory curve; S2, the virtual plane is divided into grids; S3, the grid with the point position data on the trajectory curve is extracted, and the boundary information of multiple working grids corresponding to the trajectory curve is obtained; S4, after receiving the rendering signal of the working grid, the point position data of the working grid is traversed, and the point position data of the working grid is rendered to the map; each time, only the point position data of the map region corresponding to the working grid is traversed and rendered, the data magnitude during traversal is reduced, the problem that large-scale trajectory point position data analysis is stuck and the rendering efficiency is low is solved.

Description

Technical Field

[0001] This invention relates to the field of map trajectory visualization technology, specifically to a method and medium for visualizing and analyzing large-scale trajectory point data. Background Technology

[0002] In existing technologies, there are two main methods for analyzing coordinate or trajectory data:

[0003] The first type is based on statistical analysis of pure data, which involves quantitative statistics of data from various dimensions and produces corresponding data tables or statistical reports. However, the data analysis results are not intuitive enough.

[0004] The second approach involves targeted analysis based on a single detailed or key data point, displaying all the data on the map software to intuitively reflect the analysis results. However, when the data volume of coordinates or trajectories reaches a certain level, the data interaction becomes extremely sluggish, severely impacting the rendering efficiency of point data. Summary of the Invention

[0005] The technical problem to be solved by this invention is that the visualization of large-scale trajectory point data is choppy and the rendering efficiency is low. The purpose is to provide a method and medium for visualizing and analyzing large-scale trajectory point data, thereby solving the problems of choppy analysis and low rendering efficiency of large-scale trajectory point data.

[0006] This invention is achieved through the following technical solution:

[0007] The first aspect provides a method for visualizing and analyzing large-scale trajectory point data, including the following steps:

[0008] Obtain the point dataset, plot the point dataset onto a virtual plane based on latitude and longitude, and obtain the trajectory curve;

[0009] The virtual plan view described above is divided into grids;

[0010] Extract the grid containing the point data on the above trajectory curve to obtain the boundary information of multiple working grids corresponding to the above trajectory curve;

[0011] Upon receiving a rendering signal for the aforementioned working grid, the point data of the aforementioned working grid is traversed, and the point data of the aforementioned working grid is rendered onto the map.

[0012] The virtual planar map is divided into multiple grids. Based on the point data on the trajectory curve, the working grid is extracted. The trajectory curve is then rendered onto the map sequentially according to the working grid. Each time, only the point data of the map area corresponding to the working grid is traversed and rendered, which reduces the amount of data during traversal and solves the problems of lag and low rendering efficiency in large-scale trajectory point data analysis.

[0013] Furthermore, after receiving the rendering signal of the aforementioned working grid, it is also necessary to map the boundary information of the aforementioned working grid onto the map based on the boundary information of the aforementioned working grid to obtain the map area corresponding to the aforementioned working grid.

[0014] Furthermore, the map software display range is obtained, and the map display area is obtained based on the map software display range.

[0015] Furthermore, after obtaining the map area and map display area corresponding to the above working grid, it is also necessary to determine whether the map area corresponding to the above working grid is within the map display area.

[0016] If the map area corresponding to the above working grid is in the map display area, then traverse the point data of the above working grid, render the point data of the above working grid to the corresponding map area, and mark the map area as the rendered area.

[0017] If the map area corresponding to the above working grid is not in the map display area, then determine whether the point data in the map area corresponding to the above working grid is rendered.

[0018] If the point data in the map area corresponding to the above working grid has been rendered, then clear the rendered point data in the above map area.

[0019] If the point data in the map area corresponding to the above working grid has not been rendered, then the map area is moved to the map software display area, the point data of the above working grid is traversed, the point data of the above working grid is rendered into the map area, and the map area is marked as a rendered area.

[0020] Based on the map display area, render the point data of the map area corresponding to the working grid to achieve visualization; if the map area corresponding to the working grid is not in the map display area and the map area is a rendered area, it means that the map area has been displayed. Clear the rendered point data of the map area to reduce the data volume, increase the running memory of data analysis, and improve rendering efficiency.

[0021] Furthermore, to determine whether the map area corresponding to the aforementioned working grid is within the map display area, the specific steps are as follows:

[0022] The boundary information of the aforementioned working grid includes data from multiple boundary points.

[0023] If any one or more boundary point data are in the map display area, then the map area corresponding to the above working grid is in the map display area;

[0024] If all boundary point data in the boundary information of the above working grid are not in the map display area, then the map area corresponding to the above working grid is not in the map display area.

[0025] If any of the above boundary point data is in the map display area, it can be said that the map area corresponding to the above working network is in the map display area. When determining whether the map area corresponding to the above working grid is in the map display area, it is only necessary to compare one boundary point data to find that is in the map display area to end the process. Compared with determining that every boundary point data in the above working grid is in the map display area, the number of comparisons is reduced and the rendering efficiency is improved.

[0026] Furthermore, to determine whether the point data in the map area corresponding to the above working grid has been rendered, the specific steps are as follows:

[0027] The map regions mentioned above are marked as unrendered areas before they are rendered, and as rendered areas after they are rendered. The rendering status of the map regions is determined based on the markings of the map regions mentioned above.

[0028] Furthermore, after receiving the point query signal of the aforementioned trajectory curve, the system traverses multiple of the aforementioned working grids to obtain the queried point data.

[0029] Furthermore, the number of grids is calculated based on the total amount of data at points on the aforementioned trajectory curve.

[0030] Furthermore, the formula for calculating the number of grid cells mentioned above is as follows:

[0031] N = S / M, where N represents the number of grids, S represents the total number of data points on the trajectory curve, and M represents the total number of data points in each grid.

[0032] The second aspect provides a computer-readable storage medium storing a computer program that enables a computer to execute the aforementioned large-scale trajectory point data visualization and analysis method.

[0033] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0034] The trajectory curves are drawn based on the acquired point dataset. The virtual map is divided into multiple grids. The working grids are extracted based on the point data on the trajectory curves. The trajectory curves are rendered onto the map sequentially according to the working grids. Each time, only the point data of the map area corresponding to the working grid is traversed and rendered, which reduces the amount of data during traversal and solves the problems of lag and low rendering efficiency in large-scale trajectory point data analysis. Attached Figure Description

[0035] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0036] Figure 1 The main flowchart provided for Example 1;

[0037] Figure 2 The flowchart provided in Example 1 for determining whether the map area corresponding to the working grid is within the map display area;

[0038] Figure 3 The trajectory curve from location 1 to location 2 provided in Example 2;

[0039] Figure 4 This is a virtual plan view after meshing provided in Example 2;

[0040] Figure 5 This is a virtual plan view after extracting the working grid, as provided in Example 2.

[0041] Figure 6 The map display area provided in Example 2. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0043] In all data interactions between virtual floor plans and maps, the interaction is based on point data. In computer software, querying point data requires iterating through all point data. The larger the amount of data to be iterated, the more time is spent. Therefore, this invention reduces the amount of data to be iterated, thereby optimizing query efficiency.

[0044] Example 1

[0045] This embodiment 1 provides a method for visualizing and analyzing large-scale trajectory point data, such as... Figure 1 As shown, it includes the following steps:

[0046] S1. Obtain the point dataset and plot the point dataset onto a virtual plane map according to latitude and longitude to obtain the trajectory curve;

[0047] S2. Divide the above virtual plan into a grid;

[0048] S3. Extract the grid containing the point data on the above trajectory curve to obtain the boundary information of multiple working grids corresponding to the above trajectory curve;

[0049] S4. After receiving the rendering signal of the above-mentioned working grid, traverse the point data of the above-mentioned working grid and render the point data of the above-mentioned working grid onto the map.

[0050] The virtual planar map is divided into multiple grids. Based on the point data on the trajectory curve, the working grid is extracted. The trajectory curve is then rendered onto the map sequentially according to the working grid. Each time, only the point data of the map area corresponding to the working grid is traversed and rendered, which reduces the amount of data during traversal and solves the problems of lag and low rendering efficiency in large-scale trajectory point data analysis.

[0051] In a specific embodiment, after receiving the rendering signal of the aforementioned working grid, it is also necessary to map the boundary information of the aforementioned working grid onto the map based on the boundary information of the aforementioned working grid to obtain the map area corresponding to the aforementioned working grid.

[0052] Obtain the map software display range, and based on the map software display range, obtain the map display area.

[0053] Specific implementation examples, such as Figure 2 As shown, after obtaining the map area and map display area corresponding to the above working grid, it is also necessary to...

[0054] F1. Determine whether the map area corresponding to the above working grid is within the map display area;

[0055] F2. If the map area corresponding to the above working grid is in the map display area, then traverse the point data of the above working grid, render the point data of the above working grid to the corresponding map area, and mark the map area as the rendered area.

[0056] F3. If the map area corresponding to the above working grid is not in the map display area, determine whether the point data in the map area corresponding to the above working grid is rendered.

[0057] F31. If the point data in the map area corresponding to the above working grid has been rendered, then clear the rendered point data in the above map area.

[0058] F32. If the point data in the map area corresponding to the above working grid has not been rendered, then move the map area to the map software display area, traverse the point data of the above working grid, render the point data of the above working grid to the map area, and mark the map area as a rendered area.

[0059] Based on the map display area, render the point data of the map area corresponding to the working grid to achieve visualization; if the map area corresponding to the working grid is not in the map display area and the map area is a rendered area, it means that the map area has been displayed. Clear the rendered point data of the map area to reduce the data volume, increase the running memory of data analysis, and improve rendering efficiency.

[0060] In a specific implementation, the steps for determining whether the map area corresponding to the aforementioned working grid is within the map display area are as follows:

[0061] The boundary information of the aforementioned working grid includes data from multiple boundary points.

[0062] If any one or more boundary point data are in the map display area, then the map area corresponding to the above working grid is in the map display area;

[0063] If all boundary point data in the boundary information of the above working grid are not in the map display area, then the map area corresponding to the above working grid is not in the map display area.

[0064] If any of the above boundary point data is in the map display area, it can be said that the map area corresponding to the above working network is in the map display area. When determining whether the map area corresponding to the above working grid is in the map display area, it is only necessary to compare one boundary point data to find that is in the map display area to end the process. Compared with determining that every boundary point data in the above working grid is in the map display area, the number of comparisons is reduced and the rendering efficiency is improved.

[0065] In a specific implementation, the steps for determining whether point data in the map area corresponding to the aforementioned working grid has been rendered are as follows:

[0066] The map regions mentioned above are marked as unrendered areas before they are rendered, and as rendered areas after they are rendered. The rendering status of the map regions is determined based on the markings of the map regions mentioned above.

[0067] In a specific embodiment, after receiving the point query signal of the above trajectory curve, the system traverses multiple of the above working grids to obtain the queried point data.

[0068] In a specific implementation, the number of grids is calculated based on the total amount of point data on the trajectory curve.

[0069] In a specific embodiment, the formula for calculating the number of grid cells is as follows:

[0070] N = S / M, where N represents the number of grids, S represents the total number of data points on the trajectory curve, and M represents the total number of data points in each grid.

[0071] Example 2

[0072] The data set of points from location 1 to location 2 is plotted on a virtual plan view to obtain the trajectory curve from location 1 to location 2 (e.g., Figure 3 As shown), the total number of points on the trajectory curve is 1 million. The total number of points in each grid is set to 10,000. According to the calculation formula N = S / M, the number of grids is 100.

[0073] Divide the above virtual plan into 100 grids, as follows: Figure 4 As shown;

[0074] Extract the grid containing the point data on the aforementioned trajectory curve, such as Figure 5 As shown, the boundary information of multiple working grids corresponding to the above trajectory curve is obtained;

[0075] The map display area mentioned above includes map areas 2 to 9 (e.g., map areas 2 to 9). Figure 6 As shown), working grid 1 corresponds to map region 1, working grid 2 corresponds to map region 2, working grid 3 corresponds to map region 3, working grid 4 corresponds to map region 4, working grid 5 corresponds to map region 5, working grid 6 corresponds to map region 6, working grid 7 corresponds to map region 7, working grid 8 corresponds to map region 8, working grid 9 corresponds to map region 9, and working grid 10 corresponds to map region 10. Map region 1 is marked as a rendered region, map regions 2 to 9 are marked as unrendered regions, and map region 10 is marked as an unrendered region.

[0076] Upon receiving the rendering signal of the aforementioned working grid 1, if the aforementioned map region 1 is not in the map display area and is marked as a rendered area, then the rendered point data of the aforementioned map region 1 is cleared.

[0077] or,

[0078] Upon receiving a rendering signal from any one of the working grids 2 to 9, the point data of the corresponding working grids 2 to 9 are traversed, and the point data of the working grids 2 to 9 are rendered to map regions 2 to 9. The corresponding map regions 2 to 9 are then marked as rendered regions.

[0079] or,

[0080] Upon receiving the rendering signal from the aforementioned working grid 10, the map region 10 is moved into the map software display area, the point data of the aforementioned working grid 10 is traversed, the point data of the aforementioned working grid 10 is rendered into the map region 10, and the map region 10 is marked as a rendered region.

[0081] Example 3

[0082] This embodiment 3 provides a computer-readable storage medium storing a computer program that enables a computer to execute the above-described large-scale trajectory point data visualization and analysis method.

[0083] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for visualizing and analyzing large-scale trajectory point data, characterized in that, Includes the following steps: Obtain the point dataset, plot the point dataset onto a virtual plane based on latitude and longitude, and obtain the trajectory curve; The virtual plan view is divided into grids; Extract the grid containing the point data on the trajectory curve to obtain the boundary information of multiple working grids corresponding to the trajectory curve; After receiving a rendering signal for a working grid, the point data of the working grid is traversed and rendered onto the map; after receiving a rendering signal for a working grid, the boundary information of the working grid is also mapped onto the map according to the boundary information of the working grid to obtain the map area corresponding to the working grid; the map software display range is obtained, and the map display area is obtained according to the map software display range. After obtaining the map area and map display area corresponding to the working grid, it is also necessary to determine whether the map area corresponding to the working grid is within the map display area; If the map area corresponding to the working grid is in the map display area, then the point data of the working grid is traversed, the point data of the working grid is rendered to the corresponding map area, and the map area is marked as a rendered area. If the map area corresponding to the working grid is not in the map display area, then determine whether the point data in the map area corresponding to the working grid is rendered; If the point data in the map area corresponding to the working grid has been rendered, then the rendered point data in the map area is cleared. If the point data in the map area corresponding to the working grid is not rendered, then the map area is moved to the map software display area, the point data of the working grid is traversed, the point data of the working grid is rendered into the map area, and the map area is marked as a rendered area.

2. The large-scale trajectory point data visualization and analysis method according to claim 1, characterized in that, The specific steps to determine whether the map area corresponding to the working grid is within the map display area are as follows: The boundary information of the working grid includes multiple boundary point data. If any one or more boundary point data are in the map display area, then the map area corresponding to the working grid is in the map display area; If all boundary point data in the boundary information of the working grid are not in the map display area, then the map area corresponding to the working grid is not in the map display area.

3. The method for visualizing and analyzing large-scale trajectory point data according to claim 1, characterized in that, The specific steps to determine whether the point data in the map area corresponding to the working grid has been rendered are as follows: The map region is marked as an unrendered region before it is rendered, and as a rendered region after it is rendered. The rendering status of the map region is determined based on the marking of the map region.

4. The method for visualizing and analyzing large-scale trajectory point data according to claim 1, characterized in that, After receiving the point query signal of the trajectory curve, the system traverses multiple working grids to obtain the queried point data.

5. The method for visualizing and analyzing large-scale trajectory point data according to claim 1, characterized in that, The number of grids is calculated based on the total amount of data at points on the trajectory curve.

6. The method for visualizing and analyzing large-scale trajectory point data according to claim 5, characterized in that, The formula for calculating the number of grid cells is as follows: N = S / M, where N represents the number of grids, S represents the total number of data points on the trajectory curve, and M represents the total number of data points in each grid.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that causes a computer to perform the large-scale trajectory point data visualization and analysis method as described in any one of claims 1 to 6.

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