城市规划的未来

作者:弃知先生

近年来,城市规划理论正处于量变可能引起质变的关键时期。虽然目前尚未完全实现革命性的突破,但以下三个新兴趋势展现了显著潜力,有望推动城市规划进入新的理论高度。

一、AI与城市规划融合带来的决策转型

传统的城市规划长期依靠专家经验和传统统计分析,然而随着人工智能技术的兴起,其角色已逐渐从单纯的工具转变为辅助甚至自主决策。通过大数据、深度学习和复杂系统仿真,AI能够快速发现空间数据中的隐性关联,预测城市发展趋势并优化城市布局。甄峰教授在2022/2023年中国城市规划年会上,将AI规划划分为AI辅助型、增强型、自动型和自主型四个阶段,突出了AI从支持性工具向决策角色的转变。此外,清华大学郑宇等人在2023年发表于《Nature Computational Science》的研究表明,通过深度强化学习进行城市社区空间规划,可显著提升空间效率,潜在地提高居民服务可达性。随着算法技术和数据质量的不断提升,AI的深度介入将可能彻底改变规划决策框架,推动规划师从经验导向转向数据与智能驱动,带来规划方法的质变。

二、从“以人为本”到“以生命为本”的理论转型

过去数十年,“以人为本”的思想主导了城市规划,推动城市围绕人的需求发展。但随着生态危机和气候变化的加剧,规划理论逐渐转向更宽广的视野,即强调尊重、保护乃至修复整体生态系统。这种“以生命为本”的规划方法,强调人与自然的和谐共生,将城市视为一个整体生态系统。这一趋势已在国际学术界得到广泛讨论。例如,《ScienceDirect》平台关于城市生态敏感性分析的论文提出,通过复杂适应系统理论有效推动城市基础设施的生态转型。此外,ResearchGate上的研究进一步强调生态系统服务对城市生态安全与韧性的重要作用。这一趋势若继续深化,城市规划理论将从根本上转型为以生命共同体为中心的综合空间管理体系。

三、韧性城市理论从局部防灾向系统整体韧性演进

韧性城市理论最初主要聚焦于灾害管理和应急响应,强调基础设施与硬件环境的抗灾能力。然而近年来,公共卫生事件、经济波动和气候风险的增加,使得城市韧性概念显著扩展,已逐步涵盖社会经济韧性、社区网络韧性以及制度与治理韧性等多维系统。ResearchGate上的《城市韧性:概念、影响因素及提升路径》研究系统梳理了韧性在经济、社会、生态维度上的规划诉求。此外,Frontiers发表的《气候变化背景下城市韧性评估研究进展》进一步提出了适应气候变化的定量评估框架。新冠疫情期间城市治理体系韧性的实践检验,也进一步证实了这一理论的有效性,推动城市规划向更高层次的系统治理理论发展。

总体来看,这三大前瞻趋势不仅拓宽了城市规划理论的视野,也为规划实践提供了新思路和新方法。尽管目前尚未完全实现质的飞跃,但通过进一步的跨学科融合和有效实践,这些趋势有望推动城市规划理论实现真正意义上的质的飞跃。

Emerging Trends in Urban Planning Theory
In recent years, urban planning theory has been approaching a critical point where quantitative changes could lead to qualitative breakthroughs. Although revolutionary changes have not yet fully materialized, three emerging trends show significant potential to elevate urban planning to a new theoretical height.

  1. Decision-making Transformation through AI Integration with Urban Planning
    Traditionally, urban planning has heavily relied on expert judgment and conventional statistical analysis. However, with the rise of artificial intelligence, its role has gradually evolved from mere tools to supporting and even autonomous decision-making. Utilizing big data, deep learning, and complex systems simulation, AI can swiftly uncover hidden relationships within spatial data, predict urban development trends, and optimize city layouts.
    Zhen Feng's Insights: At the 2022/2023 China Urban Planning Annual Conference, Zhen Feng categorized AI planning into four stages: AI-assisted, AI-enhanced, AI-automated, and AI-autonomous, highlighting the shift in AI's role from a supportive tool to a decision-maker.

Tsinghua University Study: A 2023 study by Yu Zheng and colleagues, published in Nature Computational Science, demonstrated that deep reinforcement learning for spatial planning of urban communities can significantly enhance spatial efficiency and potentially improve residents' accessibility to services.

As algorithms and data quality continue to improve, AI's deep integration into planning could fundamentally change decision-making frameworks, transitioning urban planners from experience-based approaches to data-driven, intelligent methodologies, marking a qualitative leap forward.
2. Theoretical Shift from "Human-Centered" to "Life-Centered"
"Human-centered" urban planning has guided city development for decades, prioritizing human needs. However, escalating ecological crises and climate change challenges have prompted a significant shift towards a broader perspective—focusing on respecting, protecting, and even restoring entire ecosystems. This "life-centered" planning approach emphasizes the harmonious relationship between humans and nature, viewing cities not merely as human habitats but as integrated ecosystems.
Academic Support: Research published on ScienceDirect highlights that ecological sensitivity analysis frameworks, based on complex adaptive systems theory, effectively support ecological urban transformation.

Ecosystem Services: Research on ResearchGate underscores the critical role of ecosystem services in urban ecological security and resilience, further exemplifying the significance of this theoretical transformation.

If this trend continues to deepen, urban planning could fundamentally transition into a comprehensive spatial management system for life communities.
3. Evolution of Urban Resilience Theory from Disaster Response to Systemic Holistic Resilience
Initially, urban resilience theory focused predominantly on disaster management and emergency response, emphasizing the resilience of infrastructure and physical environments. However, recent public health crises, economic volatility, and climate risks have significantly broadened the concept of urban resilience to encompass socioeconomic resilience, community network resilience, and institutional and governance resilience.
Multidimensional Framework: Studies published on ResearchGate, such as "Progress in Urban Resilience: Concepts, Influencing Factors, and Evaluation," systematically outline the multidimensional planning demands of resilience across economic, social, and ecological dimensions.

Climate Adaptation: Research published on Frontiers, titled "Advances in Urban Resilience Evaluation in the Context of Climate Change," proposes quantitative evaluation frameworks tailored for climate change adaptation.

Practical Validation: Practical tests of urban governance resilience during the COVID-19 pandemic further validate the effectiveness of this theory, advancing urban planning towards higher-level systemic governance.

Conclusion
Overall, these three forward-looking trends not only broaden the theoretical scope of urban planning but also inject new energy and direction into practical planning efforts. Although a complete qualitative leap has yet to occur, continued exploration and practical application of these trends may collectively drive the next fundamental transformation in urban planning. Additionally, achieving broader interdisciplinary integration at the theoretical level and promoting more effective implementation in practice will be crucial pathways for realizing the genuine qualitative evolution of urban planning theory in the future.