Abstract-Studying human movement citywide is important for understanding mobility and transportation patterns. Rather than investigating the trajectories of individuals, we employ an Eulerian approach to analyze the crowd flows among a geographical network and a social network, which are extracted from mobile phone data. We design a suite of visualization techniques to illustrate the dynamic evolutions of the flow over the networks. We contribute the design and implementation of a visual analytics system, which is called Mobility Viewer, that supports situation-aware understanding and visual reasoning of human mobility. We exemplify our approach with a real citywide data set of seven million users in two months. Index Terms-Human mobility, visual analysis, data-driven intelligent transportation system.
Reference REF presented the MobilityViewer, a suite of visual analytics methods to analyze the crowd flows in a city within a geographical and a social network, using mobile phone data.
Mobility Viewer: An Eulerian Approach for Studying Urban Crowd Flow
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Intelligent Transportation Systems
Engineering Computer Science