多源数据驱动街区空间品质提升设计方法探索——以上海城市设计挑战赛获奖方案为例
Method Exploration of Multi-source Data-driven Design of Blocks' Spatial Quality Improvement: A Case Study of the Winning Scheme of Shanghai Urban Design Challenge
陈 泳
同济大学建筑与城市规划学院 教授，博士生导师，博士
袁美伦
浙江省城乡规划设计研究院 工程师，硕士
摘要: 伴随城镇化阶段转型，提升街区空间品质正成为新时期城市设计的工作重点。同时，网络信息技术的快速发展也正在
改变传统城市设计的工作语境，为街区空间品质的提升带来更多可能性。新数据技术在街区型城市设计的应用上目前
存在着研究维度相对单一、内容不够全面等问题，难以在整体上客观反映街区空间品质及环境要素之间的有机关系。
首先，将城市设计学科的整体观与新数据技术的集成性有效融合，探讨存量更新背景下街区空间品质提升的理论内
涵、内容构成与目标理念。其次，利用多源数据组合优势，建构多维度、多要素的综合品质研究框架、设计指标体系以及
相应的技术路径。最后，以西陵家宅路、文定坊商业街坊和小陆家嘴金融商务街区为例，通过关键基础指标、问题诊断、
目标愿景、策略框架与设计成果评估等技术环节的解析，初步验证该技术方法在不同街区环境中的可应用性。
Abstract: With the transition of urbanization phases, enhancing the quality of neighborhood spaces has become a focal point of urban design in the new era. Concurrently, the rapid advancement of information technology is altering the context of traditional urban design, presenting greater possibilities for improving neighborhood space quality. Presently, the application of new data technologies in block-
type urban design suffers from relatively limited research dimensions and insufficiently comprehensive content, making it challenging
to objectively depict the organic relationship between neighborhood space quality and environmental elements holistically. This paper integrates the holistic view of urban design with the integrative capabilities of new data technology to explore the theoretical
connotations, content composition, and target concepts for enhancing neighborhood space quality amidst existing stock updates. Subsequently, leveraging the advantages of multi-source data integration, a comprehensive research framework, a design indicator system comprising multiple dimensions and factors, and corresponding technological pathways are constructed. Finally, employing Xilingjiazhai Road, Wendingfang Commercial Street Neighborhood, and Small Lujiazui Financial and Business District as examples,
the feasibility of this technological approach in diverse neighborhood environments is preliminarily validated through the analysis of
key foundational indicators, problem diagnosis, goal vision, strategy framework, and assessment of design outcomes.
关键词：多源数据；街区更新；空间品质；数据驱动设计
Keyword: multi-source data; block renewal; spatial quality; data-driven design
中图分类号：TU984
文献标识码: A
资金资助
国家 国家自然科学基金资助项目 52178023
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