Prediction of Spatiotemporal Distributions of Transient Urban Populations with Statistics Gathered by Cell Phones

摘要

There is a growing demand for data that facilitate highly accurate understanding of the spatiotemporal distribution of both moving and static occupants in urban areas. Currently, a large amount of population data are available, however none of the data provide an accurate understanding of the numbers and departure/arrival locations of moving people using detailed units of space and time. In this paper, after evaluating the advantages and disadvantages of existing population statistics, including Mobile Spatial Statistics, Konzatsu-tokei, and Person Trip survey data, we propose a method based on maximum likelihood method is investigated for using their strengths to best advantage and compensating for weaknesses. The proposed method is then validated by comparing with another flow data, which featured spatiotemporal data including departure/arrival locations, and demonstrate that the present procedure provides accurate estimates for population flows. This study makes it possible to analyse urban regions from new and never-before employed points of view by identifying the number of transient occupants and their travel directions at any time on high level of detail.