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AI-driven urban space generation and design: Progress and prospects
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Yu KONG1, 4, Feng ZHEN2, 5, *, Yunjing HUANG3, 5, Hanxin CHEN3, 5
Science & Technology Review | 2026, 44(16) : 158 - 168
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Science & Technology Review | 2026, 44(16): 158-168
• Papers •
AI-driven urban space generation and design: Progress and prospects
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Yu KONG1, 4, Feng ZHEN2, 5, *, Yunjing HUANG3, 5, Hanxin CHEN3, 5
Affiliations
  • 1School of Architecture and Design, China University of Mining and Technology, Xuzhou 221116, China
  • 2School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China
  • 3Chongqing Planning & Design Institute, Chongqing 401120, China
  • 4Key Laboratory of Urban AI and Green Built Environment of Provincial Higher Education Institutes, Nanjing 210093, China
  • 5Key Laboratory of Monitoring, Evaluation and Early Warning of Territorial Spatial Planning Implementation, Ministry of Natural Resources, Chongqing 401147, China
Published: 2026-08-28 doi: 10.3981/j.issn.1000-7857.2025.10.00109
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Artificial intelligence (AI) is increasingly becoming a key technological force driving the intelligent transformation of urban space generation and design. This paper systematically reviews research progress on the application of AI technologies from three dimensions: the identification and measurement of urban spatial elements, urban spatial planning and design, and urban spatial operation and management. Specifically, research on the identification and measurement of urban spatial elements mainly involves element perception and quantification, spatial function identification, and pattern mining; research on urban spatial planning and design focuses on support for urban design as well as the identification, evaluation, allocation, and optimization of land use; and research on urban spatial operation and management primarily covers real-time monitoring and the optimization of operations and management in areas such as transportation, energy, safety, and public services. On this basis, the paper further outlines future research directions from three perspectives: adhering to the goal of improving the human settlement environment and promoting sustainable urban development, developing new modes of AI-driven technological integration and human–AI collaboration, and improving regulatory frameworks for AI-enabled urban space generation. The study aims to provide a reference for the application of AI in urban space generation and planning practice.

artificial intelligence  /  urban space  /  space generation  /  urban design  /  urban planning
孔宇, 甄峰, 黄芸璟, 陈翰新. AI驱动下城市空间营造与设计的研究进展与展望. 科技导报, 2026 , 44 (16) : 158 -168 . DOI: 10.3981/j.issn.1000-7857.2025.10.00109
Yu KONG, Feng ZHEN, Yunjing HUANG, Hanxin CHEN. AI-driven urban space generation and design: Progress and prospects[J]. Science & Technology Review, 2026 , 44 (16) : 158 -168 . DOI: 10.3981/j.issn.1000-7857.2025.10.00109
Appendix
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Year 2026 volume 44 Issue 16
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Article Info
doi: 10.3981/j.issn.1000-7857.2025.10.00109
  • Receive Date：2025-10-28
  • Online Date：2026-09-30
  • Published：2026-08-28
Article Data
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History
  • Received：2025-10-28
  • Revised：2026-04-13
Funding
Affiliations
    1School of Architecture and Design, China University of Mining and Technology, Xuzhou 221116, China
    2School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China
    3Chongqing Planning & Design Institute, Chongqing 401120, China
    4Key Laboratory of Urban AI and Green Built Environment of Provincial Higher Education Institutes, Nanjing 210093, China
    5Key Laboratory of Monitoring, Evaluation and Early Warning of Territorial Spatial Planning Implementation, Ministry of Natural Resources, Chongqing 401147, China
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