Moving target activity heat map generation method based on geographic grid

Abstract

The invention relates to the technical field of computers, and discloses a moving target activity heat map generation method based on a geographic grid, which comprises the following steps: 1) establishing a geographic grid space; 2) establishing a storage structure corresponding to the geographic grid space; 3) calculating the effective time weight of the moving target in the geographic grid space; 4) traversing historical track points of the moving target, mapping each track point to positions p and q in the corresponding two-dimensional array A, calculating a weight r of the track point, and accumulating r into A [p] [q], wherein p is a column number and q is a row number; and 5) generating weighted track points, and performing rendering to generate a moving target activity heat map. Under the condition of massive data, the geographic grid space is used for subdividing the geographic coordinate space, the segmentation granularity of the geographic grid space is calculated accordingto the spatial span of the heat image pixel points and the historical track points, the heat map generation speed of the moving target is greatly increased, and the heat map generation operation becomes lookup-and-play.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a method for generating heat maps of moving target activities based on geographic grids. Background technique [0002] The activity heat map of mobile targets is a data visualization tool that can visually display the activity heat of mobile targets in different geographical locations. The geographic location coordinates of moving targets often change. In order to evaluate the activity heat of a single moving target in different geographic locations, the general approach is to map the historical track points of the moving target into the geographic coordinate space, and generate a count gradient centered on each point toward the edge. The descending circle, and then calculate the counts of the overlapping parts of multiple circular areas, and finally render it into a picture to form a heat map. [0003] There are two problems in the heat map generated in this way: one is that ...

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Problems solved by technology

[0003] There are two problems in the heat map generated in this way: one is that when there are many historical track points, the generation time of the heat map is relatively high; the other is that it reflects the density of track points, and the time arrangement of historical track points In the case of uniformity, it can reflect the activity area heat of the moving target. In the case of uneven time distribution of historical track points, the activity heat statistics will be distorted. The heat is too high; the number of points in the area where the track points with long time intervals are small, and the statistically obtained activity heat is too small, and there will be deviations from the perspective of the global distribution

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