Classification of the metropolitan subway stations and spheres of influence of main commercial areas in Seoul

Ki Chan Chun, Jiwon Bahk, Heeju Kim, Hyeong-Chai Jeong and Gunn Kim

Physica A: Statistical Mechanics and its Applications, 2023, vol. 609, issue C

Abstract: We classify the subway stations in the Seoul metropolitan area using smart card data. For each station, the numbers of passengers result in a 36-dimensional data set. When the numbers of passengers per hour are expressed as coordinates of perpendicular axes, the stations represented as points in 36-dimensional space are naturally classified into four groups by K-means clustering. Even after projecting the 36-dimensional data to two-dimensional data using principal component analysis, the size and components of the group remain almost the same. By analyzing the two principal axes, we obtain a relation between each classified group and its traffic flow. Then, we determine that the group with a strong commercial pattern can be divided into four main business areas. We analyze the boarding stations of passengers who alight from the stations and determine the extent of the power of the four main business areas.

Keywords: Smart card data; K-means clustering; Principal component analysis; Sphere of influence (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:609:y:2023:i:c:s0378437122009451

DOI: 10.1016/j.physa.2022.128387

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