Impact of Summer Heat on the Movement of People in Tokyo Based on Mobile Phone Location Data

Abstract

Using human flow big data from mobile phone communications, we analyzed people’s exposure to heat around Shinagawa Station in Tokyo. Point-type data tracking of each person’s movement history were collected based on the global positioning system (GPS) communication of an application. We estimated the modes of transportation based on travel speed, distance, and GPS location of each user. Expansion coefficients were calculated using mesh-type data acquired from mobile phone base stations and transportation network data were created. We conducted route searches for each person’s data and calculated the traffic volume for each mode of transportation by linking the estimated population data to network data. In August 2019, the study explored the relationship between different modes of transportation and wet-bulb globe  temperature (WBGT), revealing significant variations in pedestrian behavior, especially during holidays. The results indicated that a high WBGT leads to a decrease in walking activity and an increase in stationary behavior during holidays, suggesting that the impact of heat is more pronounced during these times than on weekdays. Walking decreased significantly with increasing WBGT at night, highlighting the need for targeted heat-mitigation strategies in urban areas. The results argue for heat countermeasures that focus on protecting weekday commuters, who are more likely to walk despite high temperatures, and promoting nighttime pedestrian activities on holidays to minimize heat exposure. This study demonstrates the importance of integrating weather conditions into urban planning and public health strategies to improve pedestrian comfort and safety in the context of rising temperatures caused by climate change.

Keywords: mobile phone location data, wet-bulb globe temperature, human behavior, adaptation, heat-mitigation strategy, urban planning