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Life between buildings from a street view image: What do big data analytics reveal about neighbourhood organisational vitality?

Author

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  • Mingshu Wang

    (University of Twente, The Netherlands)

  • Floris Vermeulen

    (University of Amsterdam, The Netherlands)

Abstract

This article uses big data from images captured by Google Street View (GSV) to analyse the extent to which the built environment impacts the survival rate of neighbourhood-based social organisations in Amsterdam, the Netherlands. These organisations are important building blocks for social life in urban neighbourhoods. Examining these organisations’ relationships with their environment has been a useful way to study their vitality. To extract data on built environment features from GSV images, we applied a deep learning model, DeepLabv3+. We then used elastic net regression to test the relationship between the built environment empirically – distinguishing between car-related, walking-related and mixed-use land infrastructure – and the survival of neighbourhood organisations. This testing approach is novel, to our knowledge not yet having been applied in Urban Studies. Besides revealing the effects of built environment features on the social life between buildings, our study points to the value of easily applicable observational big data. Data captured by GSV and other recently developed methods offer researchers the opportunity to conduct detailed yet relatively swift and inexpensive studies without resorting to overly coarse or common subjective measurements.

Suggested Citation

  • Mingshu Wang & Floris Vermeulen, 2021. "Life between buildings from a street view image: What do big data analytics reveal about neighbourhood organisational vitality?," Urban Studies, Urban Studies Journal Limited, vol. 58(15), pages 3118-3139, November.
    • Handle: RePEc:sae:urbstu:v:58:y:2021:i:15:p:3118-3139
    DOI: 10.1177/0042098020957198
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    References listed on IDEAS

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    1. Alicia N. Rambaldi & Cameron S. Fletcher & Kerry Collins & Ryan R.J. McAllister, 2013. "Housing Shadow Prices in an Inundation-prone Suburb," Urban Studies, Urban Studies Journal Limited, vol. 50(9), pages 1889-1905, July.
    2. Nikhil Naik & Ramesh Raskar & César A. Hidalgo, 2016. "Cities Are Physical Too: Using Computer Vision to Measure the Quality and Impact of Urban Appearance," American Economic Review, American Economic Association, vol. 106(5), pages 128-132, May.
    3. Amber L. Pearson & Amanda Rzotkiewicz & Jennifer L. Pechal & Carl J. Schmidt & Heather R. Jordan & Adam Zwickle & M. Eric Benbow, 2019. "Initial Evidence of the Relationships between the Human Postmortem Microbiome and Neighborhood Blight and Greening Efforts," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 109(3), pages 958-978, May.
    4. Yu Ye & Wei Zeng & Qiaomu Shen & Xiaohu Zhang & Yi Lu, 2019. "The visual quality of streets: A human-centred continuous measurement based on machine learning algorithms and street view images," Environment and Planning B, , vol. 46(8), pages 1439-1457, October.
    5. Leyden, K.M., 2003. "Social Capital and the Built Environment: The Importance of Walkable Neighborhoods," American Journal of Public Health, American Public Health Association, vol. 93(9), pages 1546-1551.
    6. Wood, Lisa & Frank, Lawrence D. & Giles-Corti, Billie, 2010. "Sense of community and its relationship with walking and neighborhood design," Social Science & Medicine, Elsevier, vol. 70(9), pages 1381-1390, May.
    7. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    8. Aghaabbasi, Mahdi & Moeinaddini, Mehdi & Shah, Muahammad Zaly & Asadi-Shekari, Zohreh, 2018. "Addressing issues in the use of Google tools for assessing pedestrian built environments," Journal of Transport Geography, Elsevier, vol. 73(C), pages 185-198.
    9. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
    10. Kamruzzaman, Md. & Wood, Lisa & Hine, Julian & Currie, Graham & Giles-Corti, Billie & Turrell, Gavin, 2014. "Patterns of social capital associated with transit oriented development," Journal of Transport Geography, Elsevier, vol. 35(C), pages 144-155.
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    Cited by:

    1. Jon Bannister & Anthony O’Sullivan, 2021. "Big Data in the city," Urban Studies, Urban Studies Journal Limited, vol. 58(15), pages 3061-3070, November.
    2. Jiayi Liu & Yanbin Li & Yanhan Xu & Castiel Chen Zhuang & Yang Hu & Yue Yu, 2024. "Impacts of Built Environment on Urban Vitality in Cultural Districts: A Case Study of Haikou and Suzhou," Land, MDPI, vol. 13(6), pages 1-26, June.
    3. Kim, Ji-Il & Yu, Chia-Yuan & Woo, Ayoung, 2023. "The impacts of visual street environments on obesity: The mediating role of walking behaviors," Journal of Transport Geography, Elsevier, vol. 109(C).
    4. Linnet Taylor, 2021. "The taming of chaos: Optimal cities and the state of the art in urban systems research," Urban Studies, Urban Studies Journal Limited, vol. 58(15), pages 3196-3202, November.

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