Computer Vision Applications for Urban Planning: A Systematic Review of Opportunities and Constraints
Marasinghe Pelige, Raveena Lakmini, Yigitcanlar, Tan, Mayere, Severine, Washington, Tracy, & Limb, Mark (2024) Computer Vision Applications for Urban Planning: A Systematic Review of Opportunities and Constraints. Sustainable Cities and Society, 100, Article number: 105047.
Open access copy at publisher website
Description
Computer vision (CV) technology, a key subset of artificial intelligence, provides powerful tools for extracting valuable insights from visual data, which is a crucial component for the urban planning process. Despite the promising potential of CV in urban planning, its applications in this context have not been thoroughly examined. This lack of scholarship represents a critical knowledge gap in our understanding of the role of CV in urban planning. This paper aims to provide a consolidated understanding in CV applications in the urban planning process and challenges urban planners face during the adoption of CV. The paper conducts a systematic literature review to tackle the questions of how is CV applied in the urban planning process, and what are the challenges in adopting CV techniques and tools for the urban planning process? The findings revealed: (a) CV could support a broad range of urban planning tasks including data collection and analysis, issue identification and prioritisation, public participation, plan design and adoption, and implementation and evaluation; (b) CV could improve decision-making through various visual information, but its limitations need to be considered, and; (c) Utilisation of CV for urban planning could support the efforts in sustainable urban development. This study informs urban policy- and plan-making circles by providing insights into the existing and prospective contributions of CV in the planning process, how CV transforms and augments planning practices, and elaborates the challenges and limitations of CV adoption.
Impact and interest:
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| ID Code: | 244421 | ||||||||
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| Item Type: | Contribution to Journal (Journal Article) | ||||||||
| Refereed: | Yes | ||||||||
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| Measurements or Duration: | 26 pages | ||||||||
| Keywords: | urban planning process, computer vision, artificial intelligence, urban sensing, image processing, sustainable urban development, urban planning | ||||||||
| DOI: | 10.1016/j.scs.2023.105047 | ||||||||
| ISSN: | 2210-6707 | ||||||||
| Pure ID: | 149665779 | ||||||||
| Divisions: | Current > QUT Faculties and Divisions > Faculty of Engineering Current > Schools > School of Architecture & Built Environment |
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| Copyright Owner: | 2023 The Author(s) | ||||||||
| Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||||||||
| Deposited On: | 09 Nov 2023 13:33 | ||||||||
| Last Modified: | 30 Sep 2026 03:50 |
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