关键词: 出租车轨迹, 社区发现, 空间结构, 深圳市

Abstract:

The concept of urban spatial structure refers to the inherent structure formed by interactions between people and places. Studying urban spatial structure (especially its dynamic characteristics) is of considerable significance for understanding and managing cities. This study characterized the long-term dynamics of an interaction-based urban spatial structure using a large-scale taxi trajectory dataset from Shenzhen, China, for May 2009 and September 2016. Spatial networks were built to model intra-city spatial interactions at different times in order to extract the dynamic spatial structure. Due to the differences between the global spatial structure and the local spatial structure of the city, two-level hierarchical spatial networks were built by separating long- and short-distance trips. The cut-off point for hierarchical partitioning was set as 5 km in both 2009 and 2016 by comparing the coefficient of determination (R ²) for the fitted probability distribution functions of the trip distances. Furthermore, the Infomap community detection algorithm was applied to detect global and local spatial communities in the network. By comparing changes in spatial communities and combining remote sensing images with planning policies, this study characterized dynamic changes in Shenzhen’s long-term multi-scale spatial structure and revealed the impacts of infrastructure construction and planning policy on the urban spatial structure. The results showed that the spatial structure of Shenzhen underwent dramatic changes from 2009 to 2016. 1) On a global scale, urban spatial structures tend to be compact. For example, numerous small spatial communities in the suburbs of Shenzhen have merged into five large spatial communities the same as planned functional clusters, which has relevance to the Shenzhen 2020 master plan. 2) The spatial form of communities has also undergone significant changes on a global scale. For example, the shape of the community connecting the Shenzhen urban area and Shenzhen airport has changed from “|” to “U”. This is related to the opening of the Guangshen Yangjian Expressway and the expansion of the Shenzhen airport, reflecting the impact of major transportation infrastructure development on the urban spatial structure. 3) On a local scale, urban spatial structures tend to develop in a polycentric manner. For example, in Shenzhen, the two spatial communities surrounding the North High-speed Rail Station and the Nanshan Center were split into multiple spatially small communities, indicating a strong relationship with major infrastructure construction and economic development. This study verified the effectiveness of Shenzhen’s administrative division adjustment, 2020 master plan, high-speed railway station, airport expansion, and arterial expressway construction from 2009 to 2016. The results provide a valuable reference for planning implementation assessment and impact assessment of infrastructure construction, providing support for urban traffic management.

Key words: Taxi trajectory, community detection algorithm, spatial structure, Shenzhen