中文摘要：

随 locationaware 技术的普遍采纳，获得个人的长顺序、巨大、高精确性的空间与时间的轨道数据在各种各样的地理研究变得日益普及。出租车的轨道数据，大多数之一广泛地使用了内部城市的旅行模式，关于两道路网络交通和旅客的旅行行为包含富有的信息。如此的数据能被用来象城市的空间结构的宏系统一样学习个人的显微镜的活动模式。这份报纸在为采矿从使 GPS 能的出租车和他们的应用获得的轨道上集中城市的变换模式。一条新奇途径被建议与很多点地点从出租车轨道数据集发现家庭旅行的空间与时间的模式。途径包含三关键步：，识别从 OD 的统计的阀值价值发现潜在地有意义的地方的基于城市的交通格子的出租车起源目的地( OD )的空间聚类聚类提取城市的工作住房结构，并且分析结果到的可视化理解空间分发和揭示城市的结构和暗示家庭变换行为的时间的趋势。有在上海的出租车轨道数据集的案例研究，中国被介绍表明并且评估建议方法。

英文摘要：

With the widespread adoption of location- aware technology, obtaining long-sequence, massive and high-accuracy spatiotemporal trajectory data of individuals has become increasingly popular in various geographic studies. Trajectory data of taxis, one of the most widely used inner-city travel modes, contain rich information about both road network traffic and travel behavior of passengers. Such data can be used to study the microscopic activity patterns of individuals as well as the macro system of urban spatial structures. This paper focuses on trajectories obtained from GPS-enabled taxis and their applications for mining urban commuting patterns. A novel approach is proposed to discover spatiotemporal patterns of household travel from the taxi trajectory dataset with a large number of point locations. The approach involves three critical steps： spatial clustering of taxi origin-destination （OD） based on urban traffic grids to discover potentially meaningful places, identifying thresh- old values from statistics of the OD clusters to extract urban jobs-housing structures, and visualization of analytic results to understand the spatial distribution and temporal trends of the revealed urban structures and implied household commuting behavior. A case study with a taxi trajectory dataset in Shanghai, China is presented to demonstrate and evaluate the proposed method.