Lun Wu

TL;DR: This research combines activity-based analysis with a movement-based approach to model the intra-urban human mobility observed from about 15 million check-in records during a yearlong period in Shanghai, China, and shows that the simulated patterns fit the observed data well.

TL;DR: The empirical findings indicate that the Erlang is a defective indicator of population distribution, whereas the number of calls serves as a better measure and this research provides an explicit clarification with respect to using call activity data for estimating population distribution.

TL;DR: The study shows that street-level imagery, as the counterpart of remote sensing imagery, provides an opportunity to infer fine-scale human activity information of an urban region and bridge gaps between the physical space and human space.

TL;DR: Wang et al. as discussed by the authors explored the spatio-temporal patterns of urban mobility on streets, cluster streets into nine types based on their dynamic functions and capacities, and investigate the possibility of uncovering urban communities using streets, and point out the complexity of streets.

TL;DR: In this paper, the properties of G‐Field models, including domain, range, and categorization, are discussed and a descriptive framework for G‐ field models is proposed.