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Big Data: The Engine to Future Cities—A Reflective Case Study in Urban Transport

Author

Listed:
  • Christopher James Pettit

    (City Futures Research Centre, University of New South Wales, Sydney 2052, Australia)

  • Simone Zarpelon Leao

    (City Futures Research Centre, University of New South Wales, Sydney 2052, Australia)

  • Oliver Lock

    (City Futures Research Centre, University of New South Wales, Sydney 2052, Australia)

  • Matthew Ng

    (City Futures Research Centre, University of New South Wales, Sydney 2052, Australia)

  • Jonathan Reades

    (Centre for Advanced Spatial Analysis, University College London, London WC1E 6BT, UK)

Abstract

In an era of smart cities, artificial intelligence and machine learning, data is purported to be the ‘new oil’, fuelling increasingly complex analytics and assisting us to craft and invent future cities. This paper outlines the role of what we know today as big data in understanding the city and includes a summary of its evolution. Through a critical reflective case study approach, the research examines the application of urban transport big data for informing planning of the city of Sydney. Specifically, transport smart card data, with its diverse constraints, was used to understand mobility patterns through the lens of the 30 min city concept. The paper concludes by offering reflections on the opportunities and challenges of big data and the promise it holds in supporting data-driven approaches to planning future cities.

Suggested Citation

  • Christopher James Pettit & Simone Zarpelon Leao & Oliver Lock & Matthew Ng & Jonathan Reades, 2022. "Big Data: The Engine to Future Cities—A Reflective Case Study in Urban Transport," Sustainability, MDPI, vol. 14(3), pages 1-15, February.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1727-:d:740947
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