利用轨迹数据提取城市居民出行时空分布特征

介绍了利用出租车轨迹数据提取城市居民出行时空分布特征的过程，包括利用数理统计的方法对出租车上下客事件基于时间进行特征分析；给出了一种融合核密度估计(KDE)与兴趣点(POI)分类的密度聚类算法，实现了出租车上下客热点区域的挖掘以及居民出行活动规律与城市功能区之间关系的发现. 研究表明:居民的出行活动特征在“工-休”日之间以及不同时段之间都表现出明显的差异，并且这种差异性与城市功能区的分布有着密切的联系. 

Extracting the temporal and spatial distribution characteristics of urban residents by using trajectory data

A process of extracting the temporal and spatial distribution characteristics of urban residents by using taxi trajectory data is introduced, including: using the method of mathematical statistics to analyze the time-based characteristics of taxi boarding and alighting events; A density clustering algorithm integrating kernel density estimation (KDE) and point of interest (POI) classification is proposed, which realizes the mining of taxi loading and unloading hot spots and the discovery of the relationship between residents' travel activity law and urban functional areas. The research shows that the trajectory characteristics of residents show obvious differences between “work-rest” days and different periods, and this difference is closely related to the distribution of urban functional areas.