基于GPS 轨迹挖掘的城市空间动态交互特征研究

对城市移动轨迹进行深入挖掘，有助于更加精细地理解城市空间动态交互特征. 以兰州市出租车GPS轨迹为基础，采用栅格方法，分析城市栅格空间的交通出行量. 以栅格为节点，以交通出行量为权重，建立动态有向加权复杂网络. 采用Infomap 算法识别城市社团结构，研究兰州市城市结构的时空演化特征，并对城市社团识别结果进行可视化分析. 研究表明，休息日和工作日城市动态时空交互存在明显差异. 工作日的城市空间交互距离和范围较大，空间交互更加紧密；休息日的空间交互范围相对较小，分裂程度较大. 高峰期和非高峰期城市空间交互也有不同，城市空间交互随时间动态变化. 研究结果可为政府管理城市，商家运营和居民出行提供决策服务.

Dynamic Interaction of Urban Space Based on GPS Trajectory Mining

Mobility trajectory mining is essential to understand the characteristics of urban spatial dynamic interaction. This paper adopts the grid method to analyze the traffic volume between urban grids based on the taxi GPS trajectory in Lanzhou City. Given nodes that represent grids and link weights that define the traffic volume of connection between them, we establish the dynamic directed weighted complex network. The Infomap algorithm is used to identify the urban community, and the spatio- temporal evolution characteristics of city structure in Lanzhou are analyzed. The visualized analyses of the urban community are presented. The results show that there is a great difference in the spatial interaction of the rest and working days. The scope of spatial interaction on the working days is larger than the rest days. On the rest days, the space interaction scope is relatively small but the degree of fragmentation is relatively large. The urban spatial interactions are also different between peak and offpeak. Urban spatial interaction changes dynamically over time. The results can provide decision-making services for government management of cities, business operations, and residents' travel.