With the rapid development of the urbanization process, the society is suffering from traffic con-gestion, air pollution and other urban problems caused by the large amount of human movement. This paper presents a visual analysis method, which integrates vehicle surveillance data, POI data to help analyze the human mobility patterns. The proposed method applies an improved DBSCAN algorithm, which divides geographical area into functional regions based on the POI data to enhance the hidden intention behind hu-man movement. Furthermore, we present the distribution and differentiation of different functional regions with BubbleSet, and visually link the human mobility patterns among different functional regions. Finally, we analyze and explore the human movement intention through the case studies. The case studies are equipped with real world data and the characteristics of the functional regions to help understand the human mobility patterns.%随着城市发展和城市人口密集化趋势的愈加明显,大量人群移动造成的交通拥堵、空气污染等城市问题日益突出; 为了直观、有效地分析人群移动现象和理解背后的语义信息,提出了一可视分析方法, 通过整合道路卡口数据和城市POI数据, 采用改进后的DBSCAN算法将区域进行功能相似性划分以增强移动模式背后的意图, 从而挖掘人群移动在数值和语义上的模式. 进一步, 基于 BubbleSet可视化展示不同功能区域的分布和差异性, 并连接不同的功能区块以展示区域之间的人群移动. 最后通过案例分析, 结合真实数据和区域功能特征, 分析和探索人群移动意图, 得到人群移动模式和功能区域之间的联系.
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