人工智能时代的国土空间规划数字化响应与实践探索
Digital Response and Practical Exploration of Territorial Spatial Planning in the Era of Artificial Intelligence
夏 凉
上海市城市规划设计研究院 上海市量子城市空间智能创新重点实验室(筹) 规划分中心 成员 空间智能规划分院院长,正高级工程师
邹 伟(通信作者)
上海市城市规划设计研究院 上海市量子城市空间智能创新重点实验室(筹) 规划分中心 成员 高级工程师,硕士,zouwei@supdri.com
秦 战
上海市城市规划设计研究院 上海市量子城市空间智能创新重点实验室(筹) 规划分中心 成员 高级工程师,硕士
摘要: 人工智能技术正加快深入各行各业,深刻改变城市规划的研究范式与方法体系,国土空间规划领域的数字化、智能化 创新转型面临前所未有的新机遇与新挑战。为应对人工智能技术支撑下的国土空间规划数字化发展要求,从范畴延 展、能力跃迁和范式变革等角度重新剖析人工智能在行业应用中的内涵逻辑。在上海量子城市全面建设和支撑下,国 土空间规划领域在技术逻辑、应用场景、生产模式等方面发生了巨大变革。在此基础上,提出量子城市赋能国土空间规 划的框架与路径,针对国土空间规划全流程,明确基础调研、规划分析、方案设计、成果生成等不同业务环节的数字化 响应。初步提出强化行业专题成果基础以减少“AI幻觉”、积极建立符合核心价值判断的技术体系、多层次建立合理合 规技术干预等建议,进一步服务城市建设、赋能超大城市空间治理,推动量子城市背景下国土空间规划变革和转型。
Abstract: In recent years, artificial intelligence technology has rapidly penetrated various industries, profoundly changing the research paradigm and methodological system of urban planning. The digital and intelligent innovation transformation in the field of territorial spatial planning is facing unprecedented new opportunities and challenges. To meet the requirements of digital development of territorial spatial planning supported by artificial intelligence technology, the research re-examines the logical connotation of artificial intelligence in industry applications from the perspectives of connotation extension, capability leap, and paradigm transformation. In the context of comprehensive construction and support for the Quantum City, the territorial spatial planning has undergone significant changes in technical logic, application scenarios, and production models. Based on this, the research proposes a framework and path for the Quantum City to empower territorial spatial planning, and for its entire process, clearly defines the digital responses for different business links, such as the basic research, planning analysis, scheme design, and outcome generation. Combined with practical work, the research initially puts forward suggestions such as strengthening the foundation of industry-specific results to reduce “AI hallucination”, actively establishing a technical system that conforms to core value judgments, and establishing reasonable and compliant technical interventions at multiple levels, in order to further serve urban construction, empower spatial governance of megacities, and promote the transformation and development of territorial spatial planning in the context of the Quantum City.
关键词:人工智能;国土空间规划;量子城市;空间治理;应用实践
Keyword: artificial intelligence; territorial spatial planning; Quantum City; spatial governance; practical application
中图分类号:TU984
文献标识码: A
刘超,黄雨嫣,蓝杰翔,等. 大模型辅助存量空间
规划的应用展望[J]. 现代城市研究,2025(8):
10-18.
Liu Chao, Huang Yuyan, Lan Jiexiang, et al.
Prospects for large models’ applications on
stock spatial renewal planning[J]. Modern Urban
Research, 2025(8): 10-18.
单振宇. 基于LLM智能体的交通系统建模研究
动态[J]. 城市交通,2025,23(6):124-126.
Shan Zhenyu. Academic dynamics on LLM-agentbased modeling of transportation systems[J]. Urban
Transport of China, 2025, 23(6): 124-126.
吴田军,骆剑承,李子琪,等. 土地空间对象化建
模与参数智能求解——以农用地为例[J]. 地理
研究,2025,44(12):3248-3269.
Wu Tianjun, Luo Jiancheng, Li Ziqi, et al. Objectoriented modeling and parameter intelligent solving
for land space: taking agricultural land as an
example[J]. Geographical Research, 2025, 44(12):
3248-3269.
孙沣楠,丛海勇,章豪,等. 融合CTGAN与机器
学习的温州市台风灾害损失评估方法研究[J].
热带地理,2026,46(3):483-494.
Sun Fengnan, Cong Haiyong, Zhang Hao, et al.
Typhoon disaster loss assessment method for
Wenzhou City by integrating CTGAN and machine
learning[J]. Tropical Geography, 2026, 46(3): 483-
494.
王存颂,黄经南,刘奇志. 老旧社区非正规公共
空间的规划策略研究——以武汉市六合社区为
例[J]. 现代城市研究,2022(4):87-94.
Wang Cunsong, Huang Jingnan, Liu Qizhi.
Planning strategies for informal public space in old
community: a case study of Liuhe Community in
Wuhan[J]. Modern Urban Research, 2022(4): 87-94.
Zhu H, Zhang W, Huang N, et al. PlanGPT: enhancing
urban planning with tailored language model and
efficient retrieval[PP/OL]. arXiv (2024-02-29)
[2026-05-14]. http://arxiv.org/abs/2402.19273.
杨俊宴,朱骁. 人工智能城市设计在街区尺度的
逐级交互式设计模式探索[J]. 国际城市规划,
2021,36(2):7-15.
Yang Junyan, Zhu Xiao. Exploration of the step-bystep interactive design mode of artificial intelligence
urban design at the block scale[J]. Urban Planning
International, 2021, 36(2): 7-15.
钮心毅,刘思涵,林诗佳,等. 大模型融入城市规
划专业工作的技术范式与模型构建 [J]. 城市规
划学刊,2026(1):21-28.
Niu Xinyi, Liu Sihan, Lin Shijia, et al. Technical
paradigm and model construction for embedding
large models into professional urban planning
practice[J]. Urban Planning Forum, 2026(1): 21-28.
熊伟,张瑶,刘金榜. 自然资源与规划智慧化建
设的技术探索与实践——以武汉市为例[J]. 自
然资源信息化,2022(5):125-131.
Xiong Wei, Zhang Yao, Liu Jinbang, et al. Technical
exploration and practice of intelligent construction
of natural resources and planning— a case of
Wuhan City[J]. Natural Resources Informatization,
2022 (5): 125-131.
Fu X, Li C, Zhai W. Using natural language
processing to read plans: a study of 78 resilience
plans from the 100 resilient cities network[J].
Journal of the American Planning Association,
2023, 89(1): 107-119.
王世福,李永豪,黄铎,等. 面向公众参与的控规
信息检索智能体构建方法与善治场景应用[J].
城市规划学刊,2026(2):26-33.
Wang Shifu, Li Yonghao, Huang Duo, et al.
Developing an intelligent agent for regulatory
planning information retrieval: applications in
collaborative governance[J]. Urban Planning
Forum, 2026(2): 26-33.
刘振华,张子培,李海军,等. 多维决策支持的交
通智能体构建与应用:助力城市交通精细化治
理[J]. 城市规划学刊,2025(增刊2):208-214.
Liu Zhenhua, Zhang Zipei, Li Haijun, et al.
Construction and application of multi-dimensional
decision support for traffic agents: facilitating finegrained urban transportation governance[J]. Urban
Planning Forum, 2025(S2): 208-214.
上海市规划和自然资源局. 上海城市空间治理
领域人工智能应用暨量子城市空间智能建设工
作实施方案(2026—2027年)[EB/OL]. (2025-
07-08)[2026-05-14]. https://www.shanghai.gov.
cn/gwk/search/content/f7e64fe836214862a36a45
54208ffe73.
Shanghai Municipal Bureau of Planning and Natural
Resources. Implementation plan for Shanghai
Quantum City spatial intelligence planning and
construction[EB/OL]. (2025-07-08)[2026-05-14].
https://www.shanghai.gov.cn/gwk/search/content/
f7e64fe836214862a36a4554208ffe73.
单卓然,李鸿飞. 人工智能影响下城乡规划机
构、技术与职业新态势及应对策略[J]. 规划师,
2018,34(11):20-25.
Shan Zhuoran, Li Hongfei. The new trend and
coping strategies of urban planning agency,
technology and profession under the impact of AI
[J]. Planners, 2018, 34(11): 20-25.
马雁秋,李志刚,黄哲,等. 人工智能应用于城市
空间研究与规划的新进展[J]. 现代城市研究,
2025(7):11-18.
Ma Yanqiu, Li Zhigang, Huang Zhe, et al. New
developments in the application of artificial intelligence in urban spatial research and planning[J].
Modern Urban Research, 2025(7): 11-18.