刘耀林, 方飞国, 王一恒. 基于手机数据的城市内部就业人口流动特征及形成机制分析——以武汉市为例[J]. 武汉大学学报 ( 信息科学版), 2018, 43(12): 2212-2224. DOI: 10.13203/j.whugis20180140
引用本文: 刘耀林, 方飞国, 王一恒. 基于手机数据的城市内部就业人口流动特征及形成机制分析——以武汉市为例[J]. 武汉大学学报 ( 信息科学版), 2018, 43(12): 2212-2224. DOI: 10.13203/j.whugis20180140
LIU Yaolin, FANG Feiguo, WANG Yiheng. Characteristics and Formation Mechanism of Intra-Urban Employment Flows Based on Mobile Phone Data-Taking Wuhan City as an Example[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 2212-2224. DOI: 10.13203/j.whugis20180140
Citation: LIU Yaolin, FANG Feiguo, WANG Yiheng. Characteristics and Formation Mechanism of Intra-Urban Employment Flows Based on Mobile Phone Data-Taking Wuhan City as an Example[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 2212-2224. DOI: 10.13203/j.whugis20180140

基于手机数据的城市内部就业人口流动特征及形成机制分析——以武汉市为例

Characteristics and Formation Mechanism of Intra-Urban Employment Flows Based on Mobile Phone Data-Taking Wuhan City as an Example

  • 摘要: 城市内部就业人口流动作为城市群体的主要移动形式,分析其特征及形成机理对城市规划、交通预测等具有重要意义。基于武汉市手机信令数据,识别职住人口分布与流动,构建城市内部就业流动网络。运用网络分析、可达性计算、逻辑回归等方法,分析城市内部就业流动的特征及其形成机制。研究表明,武汉市内部就业流动在数量上分布不均衡,大量就业流动集中于少数街道间。在空间上,就业流动随距离、可达时间增加而减少,并依地形、文化形成若干联系紧密的就业社区;以就业流出地居住人口、流入地工作人口度量的就业势能是驱动就业流动的最主要因素,而文化差异、空间不邻近、可达性差阻碍就业流动的发生。此外,不同产业特色对就业流动影响不同,商业、科教阻碍就业外流,工业吸引外来就业。

     

    Abstract: Human mobility is a cross-disciplinary research hotspot which reflects the complex man-land relationship. Understandings of the intra-urban employment population flow, as an important part of urban group mobility, are crucial for urban planning and traffic forecasting. The common use of location-awareness devices such as mobile phones enables to capture human behavioral data for analyzing intra-urban employment flow. In this paper, we attempt to characterize the employment flow and interpret its formation mechanism using mobile phone data recorded during 30 days (from June 1, 2016 to June 30, 2016) in Wuhan. Considering the spatial distribution of cellular base stations, we divide our study area into grids sized 250 m×250 m. We then adopt approaches to extract daily individual mobility information by identifying positon and duration of stagnations. Next, we propose several rules to infer in which grids people work and reside from individual mobility information we extracted and estimate the job/housing distribution as well as the employment flows between sub-districts. We then build the employment flows network, and methods such as network centrality analysis, network density analysis and community detection are applied to discover the pattern and characteristic of employment flows. Finally, we examine the influence of employment potential, traffic accessibility, spatial proximity, cultural difference and major industry on the size of employment flow between sub-districts and interpret its formation mechanism using logistic regression. The results firstly show that the number of intra-urban employment flow in Wuhan is unevenly distributed as large amounts of employment flow are concentrated in a few sub-districts. Secondly, the employment flows mainly occur in the sub-districts with good spatial proximity. It shows the distribution of the outflow employments decrease gradually as distance and accessibility time increase, and forms several employment communities (such as Hanyang, Wuchang North, Wuchang South, et al.) in the influence of geographical barriers and cultural differences. Thirdly, the employment potential measured by the resident population of the origin sub-districts and the working population of the destination sub-districts is the most important factor to increase the size of employment flow. Rather, cultural differences and poor accessibility hinder employment flow. The result also verifies that differences in major industries affect the employment flow, that commerce and education have a negative effect on the outflow of employments, but the industry attracts employments.

     

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