INVESTIGATION ON VISITING PATTERN CHANGE IN COMMERCIAL AREAS DURING COVID-19: A CASE STUDY OF 21 CITIES IN JAPAN
Keywords: COVID-19, Commercial area, Human mobility, Mobile Big Data, Time-series clustering
Abstract. During the COVID-19 pandemic, the patterns of visiting commercial areas have changed due to numerous factors, including the risk of infection and the government’s state of emergency. This study investigated human mobility changes in commercial areas of 21 cities in Japan by applying time-series clustering of mobile big data during the COVID-19 pandemic. First, the analysis revealed that the human mobility changes were found to be area-specific and were classified into five patterns according to population change captured by mobile data: decreased cluster, slightly decreased cluster, no change cluster, slightly increased cluster, and increased cluster. There were some commercial areas, which were visited by more people, compared with the pre-COVID-19 period. Second, the increased clusters revealed a high proportion of commercial facilities that provide essential services. This finding suggests that the local-scale commercial areas were essential for supporting everyday life during the COVID-19 pandemic. Third, human mobility in commercial areas was temporarily altered, but ultimately returned to the pre-COVID-19 level. Overall, the proposed method and results provide basic information for resilient urban structures in Japan.