Abstract
The overall understanding of spatial interaction and the exact knowledge of its dynamic evolution are required in the urban planning and transportation planning. This study aimed to analyze the spatial interaction based on the large-scale mobile phone data. The newly arisen mass dataset required a new methodology which was compatible with its peculiar characteristics. A three-stage framework was proposed in this paper, including data preprocessing, critical activity identification, and spatial interaction measurement. The proposed framework introduced the frequent pattern mining and measured the spatial interaction by the obtained association. A case study of three communities in Shanghai was carried out as verification of proposed method and demonstration of its practical application. The spatial interaction patterns and the representative features proved the rationality of the proposed framework.
Highlights
Shanghai, the representation of mega cities in China, has been undergoing unprecedented urban sprawl
Activity points are the intermediate results of the spatial interaction analysis
The spatial distribution of activity points depicts the fundamental state of spatial interaction
Summary
The representation of mega cities in China, has been undergoing unprecedented urban sprawl. The rapid urban expansion had significant effect on the trend of travel patterns. The daily person trips and the average trip length were estimated to go through a rapid growth in the decade. In the unparalleled process of urban sprawl, planners and operators seek access to the exact knowledge of interaction between individual behavior, urban space structure, and public transport service. The past experiences and traditional theories seem inadequate for the thorny situation
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
