Hierarchical Structure Identification and Dynamic Evolution of Urban Activity Space

This paper proposes a method to study urban activity space’s hierarchical structure and dynamic evolution based on mobile phone signaling data. Firstly, the travel network is established by identifying the travel OD using mobile phone signaling data. Then, the hierarchical community discovery algorithm is used to determine the hierarchical structure of residents’ activity space. Secondly, the concept of travel tendency is proposed to describe the internal network of activity space connections and identify activity centers at different levels of activity space. Finally, taking Shanghai as an example, the hierarchical structure of urban activity space and its dynamic evolution in other years were analyzed using mobile phone signaling data in 2011 and 2019. In addition, the spatial differentiation of urban activity space structure caused by travel distance was discussed. The results show that the spatial structure of activity space in Shanghai has become more evident during the past eight years.