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Understanding the dynamics of urban areas of interest through volunteered geographic information

Author

Listed:
  • Meixu Chen

    (University of Liverpool)

  • Dani Arribas-Bel

    (University of Liverpool)

  • Alex Singleton

    (University of Liverpool)

Abstract

Obtaining insights about the dynamics of urban structure is crucial to the framing of the context within the smart city. This paper focuses on urban areas of interest (UAOI), a concept that provides functional definitions of a city’s spatial structure. Traditional sources of social data can rarely capture these aspects at scale while spatial information on the city alone does not capture how the population values different parts of the city and in different ways. Hence, we leverage volunteered geographic information (VGI) to overcome some of the limits of traditional sources in providing urban structural and functional insights. We use a special type of VGI—metadata from geotagged Flickr images—to identify UAOIs and exploit their temporal and spatial attributes. To do this, we propose a methodological strategy that combines hierarchical density-based spatial clustering for applications with noise and the ‘α-shape’ algorithm to quantify the dynamics of UAOIs in Inner London for a period 2013–2015 and develop an innovative visualisation of UAOI profiles from which UAOI dynamics can be explored. Our results expand and improve upon the previous literature on this topic and provide a useful reference for urban practitioners who might wish to include more timely information when making decisions.

Suggested Citation

  • Meixu Chen & Dani Arribas-Bel & Alex Singleton, 2019. "Understanding the dynamics of urban areas of interest through volunteered geographic information," Journal of Geographical Systems, Springer, vol. 21(1), pages 89-109, March.
  • Handle: RePEc:kap:jgeosy:v:21:y:2019:i:1:d:10.1007_s10109-018-0284-3
    DOI: 10.1007/s10109-018-0284-3
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    Citations

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    Cited by:

    1. Rico H Herzog & Juliana E Gonçalves & Geertje Slingerland & Reinout Kleinhans & Holger Prang & Frances Brazier & Trivik Verma, 2024. "Cities for citizens! Public value spheres for understanding conflicts in urban planning," Urban Studies, Urban Studies Journal Limited, vol. 61(7), pages 1327-1344, May.
    2. Yang, Yitao & Jia, Bin & Yan, Xiao-Yong & Li, Jiangtao & Yang, Zhenzhen & Gao, Ziyou, 2022. "Identifying intercity freight trip ends of heavy trucks from GPS data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    3. Pattama Krataithong & Chutiporn Anutariya & Marut Buranarach, 2022. "A Taxi Trajectory and Social Media Data Management Platform for Tourist Behavior Analysis," Sustainability, MDPI, vol. 14(8), pages 1-18, April.

    More about this item

    Keywords

    Urban dynamics; Urban areas of interest; Quantitative analysis; Volunteered geographic information; Social media data;
    All these keywords.

    JEL classification:

    • R0 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General

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