i-tStar: Interactive Trajectory Star Coordinates

Jing He, Lingxiao Li, Xin Wang
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Abstract

There are many sources of geographic big data, and most of them come from heterogeneous environments. As the techniques evolved, these data sources contain attribute information of different spatial scales, time scales and complexity levels. In this case, visualizing high-dimensional spatiotemporal trajectory data is extremely challenging. Therefore, we propose a new solution, trajectory behavior feature, for moving objects that are integrated into a view to display and extract spatiotemporal patterns.
i-tStar:交互轨迹星坐标
地理大数据的来源很多,大部分来自异构环境。随着技术的发展,这些数据源包含了不同空间尺度、时间尺度和复杂程度的属性信息。在这种情况下,可视化高维时空轨迹数据是极具挑战性的。因此,我们提出了一种新的解决方案——轨迹行为特征,将运动对象集成到视图中,以显示和提取时空模式。
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