Measuring visual quality of street space and its temporal variation: Methodology and its application in the Hutong area in Beijing
Measuring visual quality of street space and its temporal variation: Methodology and its application in the Hutong area in Beijing
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街道空间视觉质量及其时间变化测量：方法及其在北京胡同地区的应用
DOI：
10.1016/j.landurbplan.2018.09.015
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发表时间：
2019-11-01
影响因子：
9.1
通讯作者：
Long, Ying
中科院分区：
文献类型：
--
作者：
Tang, Jingxian;Long, Ying
虽然人们都知道，街道空间的质量在促进城市活力中起着至关重要的作用，但如何在大范围内定量测量它仍然没有达成共识。最近出现的数据集街景图片揭示了克服以前的限制的可能性，从而提出了一个研究范式的转变。利用这一优势，本文探索了一种大区域街道空间视觉质量评价和变化识别的新方法。选取北京历史街区空间的典型代表--胡同进行实证研究。在实验部分，我们采集了多年来覆盖所有胡同的腾讯街景图片，并进行了物理和感知视觉质量评估。利用机器学习分割方法SegNet对绿地、开放性、围合性进行三维构成计算，结合对街墙连续性和断面比例的二维分析，自动获得街道空间的物理视觉质量;通过停留意愿评分从5个方面对街道空间的感知视觉质量进行评价。基于所识别的物理空间变化来评估质量的变化。结果表明，胡同的视觉质量不理想，而历史保护街区的一些更新项目的视觉质量较好。大多数胡同缺乏视觉上的绿色，相对较连续，但断面率较低。主干道附近的胡同见证了机动化的增长趋势。物理质量和感知质量的差异表明了自动计算方法的可行性和局限性。最近3-4年，改善的胡同不到2.5%，主要是缓慢的美化。
Although it is widely known that quality of street space plays a vital role in promoting urban vibrancy, there is still no consensus on how to quantitatively measure it for a large scale. Recent emerging dataset Street View Picture has revealed the possibility to overcome the previous limit, thus bringing forward a research paradigm shift. Taking this advantage, this paper explores a new approach for visual quality evaluation and variation identification of street space for a large area. Hutongs, which typically represent for historical street space in Beijing, are selected for empirical study. In the experimental part, we capture multi-years Tencent Street View Picture covering all the Hutongs, and conduct both physical and perceived visual quality evaluation. The physical visual quality of street space is achieved automatically by combining 3-dimensional composition calculation of greenery, openness, enclosure using machine-learning segmentation method SegNet, and 2-dimensional analysis of street wall continuity and cross-sectional proportion; perceived visual quality of street space is evaluated by stay willingness scoring from five aspects. The variation of quality is evaluated based on the identified physical space variations. The result indicates that visual quality of Hutongs are not satisfied, while some regeneration projects in the historical protection block is better. Most Hutongs are in shortage of visual green, relative more continuous but with low cross-sectional ratio. Hutongs near main road witness an increasing trend of motorization. The difference between physical and perceived quality indicates the feasibility and limitation of the auto-calculation method. In the most recent 3-4 years, less than 2.5% Hutongs are improved, which are mainly slow beautification.