IDEAS home Printed from https://ideas.repec.org/a/sae/envirb/v52y2025i1p131-149.html

Quantitative measurement of urban spatial vitality by integrating physical built environment and subjective perception dimensions

Author

Listed:
  • Shaojun Liu
  • Yi Long
  • Ling Zhang
  • Jing Yang
  • Wenfei Dong

Abstract

Urban space vitality is a critical indicator for supporting rational urban spatial planning and updating and formulating sustainable development strategies. However, in many areas (e.g., aging urban areas), there is often a mismatch between the conditions of the physical built environment and its spatial attractiveness. Traditional methods based on physical space design theory often fail to accurately measure the spatial vitality of these areas. Street view images directly reflect the actual construction situation and effectively compensate for the lack of visual, subjective, perception dimension information. This study proposes a novel method that integrates objective and subjective dimensions to measure urban vitality, which is captured by incorporating spatial data of points of interest, building outlines, road networks, and street view images. Then, taking mobile phone signaling data as a source of ground truth validation, we choose Nanjing as a case study to demonstrate that our multidimensional fusion method exhibits higher explanatory power and better alignment with actual conditions by comparing it against single-dimensional methods. The results underscore the importance of integrating subjective and perceptual dimensions in measurements of urban vitality. We believe that the localized samples of the subjective perception survey will further enhance the accuracy and generalizability of this method in the future.

Suggested Citation

  • Shaojun Liu & Yi Long & Ling Zhang & Jing Yang & Wenfei Dong, 2025. "Quantitative measurement of urban spatial vitality by integrating physical built environment and subjective perception dimensions," Environment and Planning B, , vol. 52(1), pages 131-149, January.
  • Handle: RePEc:sae:envirb:v:52:y:2025:i:1:p:131-149
    DOI: 10.1177/23998083241256704
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/23998083241256704
    Download Restriction: no

    File URL: https://libkey.io/10.1177/23998083241256704?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Li Shen & Peter R. Stopher, 2014. "Review of GPS Travel Survey and GPS Data-Processing Methods," Transport Reviews, Taylor & Francis Journals, vol. 34(3), pages 316-334, May.
    2. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    3. Philip Salesses & Katja Schechtner & César A Hidalgo, 2013. "The Collaborative Image of The City: Mapping the Inequality of Urban Perception," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-12, July.
    4. Zhang, Yonglin & Li, Shanlin & Dong, Rencai & Deng, Hongbing & Fu, Xiao & Wang, Chenxing & Yu, Tianshu & Jia, Tianxia & Zhao, Jingzhu, 2021. "Quantifying physical and psychological perceptions of urban scenes using deep learning," Land Use Policy, Elsevier, vol. 111(C).
    5. Yang Xu & Shih-Lung Shaw & Ziliang Zhao & Ling Yin & Zhixiang Fang & Qingquan Li, 2015. "Understanding aggregate human mobility patterns using passive mobile phone location data: a home-based approach," Transportation, Springer, vol. 42(4), pages 625-646, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sarah Williams & Elizabeth Currid-Halkett, 2014. "Industry in Motion: Using Smart Phones to Explore the Spatial Network of the Garment Industry in New York City," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-11, February.
    2. Galdo, Virgilio & Li, Yue & Rama, Martin, 2021. "Identifying urban areas by combining human judgment and machine learning: An application to India," Journal of Urban Economics, Elsevier, vol. 125(C).
    3. Mariem Fekih & Tom Bellemans & Zbigniew Smoreda & Patrick Bonnel & Angelo Furno & Stéphane Galland, 2021. "A data-driven approach for origin–destination matrix construction from cellular network signalling data: a case study of Lyon region (France)," Transportation, Springer, vol. 48(4), pages 1671-1702, August.
    4. Xiaoli Hao & Yuhong Li & Ume Lail, 2022. "Sustainable development with city, industry, economic and environment: The role of city-industry integration on green economic growth," Journal of Regional Economics, Anser Press, vol. 1(1), pages 1-23, December.
    5. Xu, Jiwei & Liu, Yaolin & Liu, Yanfang & An, Rui & Tong, Zhaomin, 2023. "Integrating street view images and deep learning to explore the association between human perceptions of the built environment and cardiovascular disease in older adults," Social Science & Medicine, Elsevier, vol. 338(C).
    6. Davenport, Sally, 2005. "Exploring the role of proximity in SME knowledge-acquisition," Research Policy, Elsevier, vol. 34(5), pages 683-701, June.
    7. Mark Partridge & M. Rose Olfert & Alessandro Alasia, 2007. "Canadian cities as regional engines of growth: agglomeration and amenities," Canadian Journal of Economics, Canadian Economics Association, vol. 40(1), pages 39-68, February.
    8. João Juchem Neto & Julio Claeyssen, 2015. "Capital-induced labor migration in a spatial Solow model," Journal of Economics, Springer, vol. 115(1), pages 25-47, May.
    9. Arcalean, Calin & Glomm, Gerhard & Schiopu, Ioana, 2012. "Growth effects of spatial redistribution policies," Journal of Economic Dynamics and Control, Elsevier, vol. 36(7), pages 988-1008.
    10. Marcel Bednarz & Tom Broekel, 2020. "Pulled or pushed? The spatial diffusion of wind energy between local demand and supply," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 29(4), pages 893-916.
    11. Joan R Rosés & Nikolaus Wolf, 2021. "Regional growth and inequality in the long-run: Europe, 1900–2015," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(1), pages 17-48.
    12. Emma Howard, 2017. "Social networks, geographic proximity, and firm performance in Vietnam," WIDER Working Paper Series wp-2017-69, World Institute for Development Economic Research (UNU-WIDER).
    13. Ingrid Ott & Susanne Soretz, 2006. "Governmental activity, integration, and agglomeration," Working Paper Series in Economics 57, University of Lüneburg, Institute of Economics.
    14. Gao, Ting, 2004. "Regional industrial growth: evidence from Chinese industries," Regional Science and Urban Economics, Elsevier, vol. 34(1), pages 101-124, January.
    15. María Ayuda & Fernando Collantes & Vicente Pinilla, 2010. "From locational fundamentals to increasing returns: the spatial concentration of population in Spain, 1787–2000," Journal of Geographical Systems, Springer, vol. 12(1), pages 25-50, March.
    16. Vasco Leite & Sofia Castro & João Correia-da-Silva, 2009. "The core periphery model with asymmetric inter-regional and intra-regional trade costs," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 8(1), pages 37-44, April.
    17. Sidney Turner & Richard Turner, 2011. "Capital cities: a special case in urban development," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 46(1), pages 19-35, February.
    18. Agarwalla, Astha, 2011. "Agglomeration Economies and Productivity Growth in India," IIMA Working Papers WP2011-01-08, Indian Institute of Management Ahmedabad, Research and Publication Department.
    19. Masashige Hamano & Pierre M. Picard, 2017. "Extensive and intensive margins and exchange rate regimes," Canadian Journal of Economics, Canadian Economics Association, vol. 50(3), pages 804-837, August.
    20. Michael Beenstock & Daniel Felsenstein, 2003. "Decomposing the Dynamics of Regional Earnings Disparities in Israel," ERSA conference papers ersa03p90, European Regional Science Association.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:envirb:v:52:y:2025:i:1:p:131-149. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.