Upgrading Spatiotemporal Demographic Data by the Integration of Detailed Population Attributes

Abstract. In this study, a method was constructed for adding value to spatiotemporal data by integrating demographic information obtained from Mobile Spatial Statistics (MSS), Person-trip (PT) data, and the national census. We first constructed a model that provided spatiotemporal distribution of occupants in urban areas that vary according to clock time, location, and building use classification. The time, location, and building use classification were employed as keys to integrate demographic information. Weekday and weekend data for the central wards of Tokyo were employed to create estimates of the number of occupants with their detailed attributes. Using numerical examples, we demonstrated that the proposed model can provide demographic spatiotemporal distributions with far higher value than before; in which the buildings people occupy, their reasons for being there, their sex and age bracket, and their residential locations, can all be identified.