Visual Analysis of Steady-State Human Mobility in Cities

Cities are living systems where urban infrastructures and their functions are defined by and evolved with population behavior. Visualizing, profiling, and comparing the mobility behavior of the population has been challenging because of the enormous population size in modern cities (tens of millions in our dataset). This paper proposes a steady-state visual analysis of human mobility that abstracts the longitudinal trajectory of each city resident into five information-theoretic metrics: Fluidity, vibrAncy, Commutation, divErsity, and densiTy (FACET). The metrics characterize the long-term mobility behavior of residents concerning municipal structures and points of interest in the city and can also be aggregated to profile underlying city regions. Based on the steady-state analysis method, we develop a visualization system, namely UrbanFACET, which provides a multifaceted panorama of human mobilities in cities and helps to compare urban functions among cities and time. We evaluate the proposed method and system through case studies in real-world big cities. Our result demonstrates the effectiveness of the steady-state analysis in several target domains such as urban planning, business site configuration, and city security surveillance.