EPJ Data Science (Aug 2021)
Spatiotemporal distributions of population in Seoul: joint influence of ridership and accessibility of the subway system
Abstract
Abstract Moving along with daily life, urban residents and commuters create characteristic spatiotemporal patterns which vary extensively with the time of day. These patterns are formed via traffic flows: accordingly, understanding the impact of transportation system is essential for urban planners to evaluate expected urban activities. To explore them, we examine specifically population distributions in Seoul City by analyzing hourly population data based on mobile phone location records in combination with a couple of indicators of the Seoul Subway system. Through clustering and principal component analyses, we first demonstrate that the spatial distribution of the population is categorized according to the time of day, i.e., night, daytime, and evening, variations across which reflect the morphology of land use. We then examine the influence of the subway system on the population, employing ridership and accessibility as indicators. Our linear regression analysis shows that both are associated with the daytime and the evening populations, which implies that only commercial activities are substantially coupled to the subway system. Further, we find that the distinctive difference of night population is encoded in the probability distributions; this is elucidated by means of a multiplicative growth model for the morphological evolution of Seoul, revealing decentralization of residential areas and centralization of commercial areas. This study sheds light on the interplay of a public transportation system and land use, which is of relevance to planners and policymakers wishing to develop neighborhoods in support of sustainable modes.
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