杨天人 吴志强 潘起胜 曲峻熙 金鹰

Yang Tianren, Wu Zhiqiang, Pan Qisheng, Qu Junxi, Jin Ying

关键词：城市系统；城市模型；规划决策系统；空间规划；城市未来；预测方法

Keywords：Urban System; Urban Model; Planning Support System; Spatial Planning; Urban Future; Prediction Method

摘要：

如何对城市的未来进行科学有效的预测是城乡规划学术研究、学科发展与空间实践所面临的长期挑战。本文从城市模型的研究进展出发，对主流城市模拟与预测方法（宏观模型、微观模型和集成模型）进行梳理归纳和优缺点述评。基于对社会经济发展与科学技术创新的趋势辨析，本文凝练了城市模型在大数据兴起、科技与行为演变、政策需求多元化、复杂科学发展中面临的挑战和机遇，并进一步提出了城市模拟与预测的发展方向，包括精细化模型的构建、对未来技术与行为变革的表述、对跨尺度与多维度交互机制的探索以及对模型结果的追踪评估与动态修正。通过对城市模型领域的综述和展望，本文希望推动城市模拟与预测的理论发展和实践创新，以更好地解决与城市发展相关的科学问题，并更有效地支撑规划的编制和评估。

Abstract：

Providing a convincing prediction for the urban future remains a challenge in planning research, discipline development and spatial practices. This paper reviews the progress in the research practice of urban models, evaluates the mainstream methods (i.e., macro, micro and integrated models) and highlights their strengths and weaknesses. Based on the identified trends in socioeconomic development and technological innovation, the challenges and opportunities of urban modelling are summarised against the backdrop of emerging big data, evolving technologies and behaviours, diversified policy needs, and growing complexity sciences. Furthermore, the future research directions of urban modelling are proposed, including the refinement of models, representation of technical and behavioural changes, model integrations across spatial scales and urban sectors, and ex-post evaluations and model updates. The findings from this research will help promote urban development theories and planning practices, since the improvements in urban models can establish a more convincing evidence base to address urban issues and support plan-making and evaluation.

杨天人，香港大学建筑学院，助理教授；香港大学深圳研究院，副研究员。tianren@hku.hk

吴志强（通信作者），中国工程院院士，同济大学建筑与城市规划学院，教授

潘起胜，美国得克萨斯大学阿灵顿分校公共政策与城市规划学系，同济大学建筑与城市规划学院，教授

曲峻熙，香港大学建筑学院，研究助理

金鹰，剑桥大学马丁建筑与城市研究中心，教授

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