OPEN ACCESS
For "polycentric" urban systems, the role of city centers and their human flows’s spatial influence on the surrounding area remain a challenging problem with many applications ranging from transportation planning to epidemiology. Firstly, we segmented urban area to different districts as the basic research unit and abstract latent activity contexts from large scale call logs in city using existing approaches. By proposing urban area as a inter-district network model of which edge is measured by temporal-spatial proximity among different districts stem from those latent activity contexts, we identified core districts of city by using a network-based method based on community detection and local centrality. We further analyzed the functional role of these core districts in city. It provides a feasible approach to uncover spatial structure of an urban system.
City’s core districts, community detection, human activity
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