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Revisiting the valuable locales in our cities? Visualizing social interaction potential around metro station areas in Wuhan, China

Author

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  • Jiangyue Wu

    (Department of Urban Planning and Design, 25809The University of Hong Kong, Pok Fu Lam, Hong Kong, China)

  • Jiangping Zhou

    (Department of Urban Planning and Design, 25809The University of Hong Kong, Pok Fu Lam, Hong Kong, China)

  • Hanxi Ma

    (Department of Urban Planning and Design, 25809The University of Hong Kong, Pok Fu Lam, Hong Kong, China)

Abstract

A complete tour of metro users consists of their journeys inside the carriage and various activities outside the carriage, in particular, those in or around metro station areas (MSAs). To fathom out the spatiality and magnitude of those activities, which involve substantial interactions among people or with urban spaces, we assume that (a) metro users who spent 30 min or more together in or around the same MSA would physically interact with at least another person there; (b) the more an MSA sees metro riders co-presenting there the higher social interaction potential (SIP) there is; (c) SIP of an MSA is positively correlated with the number of distinct riders co-presenting in that MSA. By exploiting two-day metro smartcard data of Wuhan, China, we use the number of distinct riders co-presenting in that MSA to measure and visualize the MSA-level SIP in that city. Our visuals show the SIP varies across MSA and time of the day. Some MSAs have higher SIP in the daytime whereas other MSAs have higher SIP at the nighttime. Few MSAs continuously have high SIP. These results inform us where and when SIP would be the highest and the lowest across MSAs, which can facilitate metro operators’ monitoring and management of MSAs on the one hand and help businessmen and officials decide where and when to provide services and/or sell products across MSAs.

Suggested Citation

  • Jiangyue Wu & Jiangping Zhou & Hanxi Ma, 2022. "Revisiting the valuable locales in our cities? Visualizing social interaction potential around metro station areas in Wuhan, China," Environment and Planning A, , vol. 54(3), pages 433-436, May.
    • Handle: RePEc:sae:envira:v:54:y:2022:i:3:p:433-436
    DOI: 10.1177/0308518X211062227
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    References listed on IDEAS

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    1. Neema Nassir & Mark Hickman & Zhen-Liang Ma, 2015. "Activity detection and transfer identification for public transit fare card data," Transportation, Springer, vol. 42(4), pages 683-705, July.
    2. Ingvardson, Jesper Bláfoss & Nielsen, Otto Anker, 2018. "How urban density, network topology and socio-economy influence public transport ridership: Empirical evidence from 48 European metropolitan areas," Journal of Transport Geography, Elsevier, vol. 72(C), pages 50-63.
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