IEEE Trans Vis Comput Graph. 2016 Jan;22(1):11-20. doi: 10.1109/TVCG.2015.2468111.
Learning more about people mobility is an important task for official decision makers and urban planners. Mobility data sets characterize the variation of the presence of people in different places over time as well as movements (or flows) of people between the places. The analysis of mobility data is challenging due to the need to analyze and compare spatial situations (i.e., presence and flows of people at certain time moments) and to gain an understanding of the spatio-temporal changes (variations of situations over time). Traditional flow visualizations usually fail due to massive clutter. Modern approaches offer limited support for investigating the complex variation of the movements over longer time periods.
了解更多关于人们移动性的信息对于官方决策者和城市规划者来说是一项重要任务。移动性数据集描述了随着时间的推移，人们在不同地点的存在变化以及人们在地点之间的流动（或流动）。由于需要分析和比较空间情况（即特定时间点的人员存在和流动）以及了解时空变化（随着时间的变化情况），因此移动性数据分析具有挑战性。传统的流量可视化通常由于大量混乱而失败。现代方法对于调查较长时间内运动的复杂变化提供的支持有限。
