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| 城市交通热点区域的空间交互网络分析 | |
| 引用本文： | 秦昆,周勍,徐源泉,徐雯婷,罗萍.城市交通热点区域的空间交互网络分析[J].地理科学进展,2017,36(9):1149-1157. |
| 作者姓名： | 秦昆 周勍 徐源泉 徐雯婷 罗萍 |
| 作者单位： | 1. 武汉大学遥感信息工程学院,武汉 430079 2. 地球空间信息技术协同创新中心,武汉 430079 3. 广州市城市规划勘测设计研究院,广州 510060 |
| 基金项目： | 国家重点研发计划项目(2017YFB0503604);国家自然科学基金项目(41471326) |
| 摘 要： | 城市热点区域是人们频繁活动的体现,利用人们的出行可构建空间交互网络。目前的相关研究主要集中于对热点提取方法及其动态变化的研究,对交通热点的交互作用及其构成的空间交互网络的研究还很少。本文以武汉市的出租车轨迹为数据源,利用基于时空数据场的聚类方法提取城市交通热点区域;基于复杂网络理论与方法,分析城市交通热点区域之间的空间交互作用。通过研究发现：①节假日,热点区域之间的往返交互较多;工作日,热点区域之间的交互较少;②节假日,影响力较大的节点为车站、机场等;工作日,影响力较大的节点是社区和工作地;③社团探测发现,工作日跨越长江的交互较多,非工作日跨越长江的交互较少。上述研究结论可为交通管理部门针对节假日和工作日分别制定不同的交通管理政策和方法提供参考。 |
| 关 键 词： | 城市交通热点 空间交互网络 复杂网络 社区探测 轨迹聚类 时空数据场 武汉市 |
Spatial interaction network analysis of urban traffic hotspots |
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| Kun QIN,Qing ZHOU,Yuanquan XU,Wenting XU,Ping LUO.Spatial interaction network analysis of urban traffic hotspots[J].Progress in Geography,2017,36(9):1149-1157. | |
| Authors: | Kun QIN Qing ZHOU Yuanquan XU Wenting XU Ping LUO |
| Institution: | 1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China 2. Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China 3. Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China; |
| Abstract: | Urban traffic hotspots refer to the areas where residents visit frequently. Travels of urban residents generate interactions between urban areas, which form a spatial interactive network. Existing research mainly focuses on hotspot extraction and their dynamic change, but there are few studies that examine the interaction of traffic hotspots and the spatial interaction network. Based on the taxi trajectory data in Wuhan City, we detect the urban traffic hotspots by spatiotemporal data field clustering and further analyze the spatial interaction among urban hotspots based on the complex network theory. The results show that: (1) There is a large amount of interaction between the hotspots on holidays, and less interaction between the hotspots on weekdays; (2) The nodes with great influence are the bus and train stations, airports, and so on, on holidays, and the nodes with great influence are normally residential communities, workplace, and so on, on weekdays; (3) The results of community detection found that there is more interaction across the Yangtze River on weekdays, and little interaction across the Yangtze River on holidays. The study results can provide a reference for traffic management to develop different management strategies and methods for holidays and workdays. Investigating the interaction of human behaviors with urban environment, transportation, and geographical regions from the viewpoint of spatial interaction network is an innovative interdisciplinary research field crossing geographical information science, management science, and humanities and social sciences |
| Keywords: | urban traffic hotspots spatial interaction network complex network community detection rajectory clustering spatiotemporal data field Wuhan City |
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