Abstract
This study analyzes the spatiotemporal changes of bus network clusters before and after COVID-19 with the purpose of exploring areas with high potential for the spread of infectious diseases. As the analysis method, the statistic was used, which is an extension of the Getis and Ord statistic to spatial network framework. Since statistical calculation is applied for individual flows in the bus transportation network, a parallel computing method and a supercomputer hardware are applied for the large-scale operations. The result is as follows: First, bus flows in networks are concentrated in limited places during COVID-19. Second, during COVID-19, bus uses to residential and agricultural areas increased, and bus uses to commercial and transportation areas decreased. Third, unlike other CBD clusters, no significant changes were observed in bus flow in Gangnam before and during COVID-19. This study presents the first analysis and identification of bus network cluster before and during COVID-19 in Korea.
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