Evaluating Spatial and Temporal Characteristics of Population Density Using Cellular Data

Danni Lu, Ye Li, Feng Guo

Abstract: Using 1.1 billion cellphone records collected in the city of Shanghai, this study evaluates the spatial and temporal movement of population during morning peak hours. The spatial autocorrelation of population density is quantitatively evaluated and visualized using Kriging models. We identify top traffic attraction zones (TTAZs) through population density change and evaluate the spatial and temporal characteristics of trip segments to TTAZs. The results show that the population density changes from a relatively homogenous pattern to a heterogeneous pattern during morning peak hours. Travelers are 10.65 to 17.2 times more likely to come from inside the TTAZs. Factors that affect the origins include the distance to a TTAZ, geographical separation, and metro lines. Approximately 85% of travelers arrive at their destination in a TTAZ after 8:00 a.m. The population density is higher along metro and expressway corridors and the impact increases over time during peak hours. The methodology provides a quantitative measure of the spatial and temporal characteristics of how population migrates. The study provides crucial information on the origin, arrival time, and route of trips to a TTAZ during morning peak hours. The results provide useful information to facilitate traffic management and planning in megacities and demonstrate the potential of using novel cellphone data for traffic planning and management.