摘要: |
随着城市化进程步入“下半场”,日益提升的空间
品质需求对街道空间宜步行性提出了更高要求。但目前传统的
城市更新与设计手法已难以满足人本尺度的精准设计与导控需
求,亟须立足于公众感知的精准更新与介入。以广州新、旧城
区2类典型街道为案例,立足新技术开展具身循证型的精准分
析。一方面基于虚拟现实技术和可视化陈述性偏好法,从主观
视角计算各类街道空间特征要素的宜步行性效用水平。另一方
面,结合生理传感器技术从客观视角开展建成环境评估,形成
对主观视角结论的补充。基于上述两方面,系统性地构建街道
空间界面要素与宜步行性的关联性模型,为街道空间的宜步行
性提升提供人本尺度的精细化支持,探索数据支持下的人本视
角街道设计精准化提升路径 |
关键词: 风景园林 城市设计 虚拟现实 生理传感器 街道空间品质 定量化测度 |
DOI: |
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基金项目: |
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The Measurements of Fine-scale Street Walkability and Precise Design Control: An Evidence-based Approach Based on Virtual Reality and Wearable Bio-sensors |
CHEN Zhimin,HUANG Rong,HUANG Ying,CHEN Zheng,YE Yu |
Abstract: |
Accompanying with China's further urbanization, the
public's increasing demand on spatial quality brings the rising call of
street walkability. Nevertheless, current urban design is difficult to
achieve the human-based precise design and guidance needs. In this
context, it is important to achieve precise urban design interventions
based on the public's perceptions. As a response to this situation,
this study attempts to conduct an accurate, evidence-based analysis
based on new analytical tools. Two typical streets in Guangzhou's
old and new urban areas are selected as research cases. On one
hand, the combination of virtual reality and stated preference is
applied to measure the walkability utility of various street space
features from the subjective perspective. On the other hand, built
environment audit is achieved via wearable biosensors from the
objective perspective to verify and further develop the previous
results. This analytical approach integrating both subjective and
objective perspectives help to build a statistical model between
elements of street interface and walkability systematically. The
insights achieved in this process helps to provide fine-scale support
of street walkability improvement, which illustrates the emerging of
a data-informed street design approach. |
Key words: landscape architecture urban design virtual reality biosensor street spatial quality quantitative measurement |