Revitalizing historic districts: Identifying built environment predictors for street vibrancy based on urban sensor data
Revitalizing historic districts: Identifying built environment predictors for street vibrancy based on urban sensor data
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DOI：
10.1016/j.cities.2021.103305
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发表时间：
2021-06-16
期刊：
影响因子：
6.7
通讯作者：
Zhou, Jiangping
中科院分区：
文献类型：
--
作者：
Li, Miaoyi;Liu, Jixiang;Zhou, Jiangping
活力对于历史街区的振兴是不可或缺的，也是有益的。因此，确定建筑环境活力的预测因子是城市从业者和政策制定者非常感兴趣的问题。然而，这是具有挑战性的。一方面，在选择合适的活力代理方面没有达成共识。另一方面，建筑环境是多维的，但有限的研究同时从不同的维度考察了它对振动的影响。中国，白塔寺地区是北京典型的历史街区。本研究基于CityGrid传感器产生的长期重复测量数据集，研究了白塔斯地区街道活力的时空分布，并检验了两个季节(即夏秋冬季)的建成环境预测因子，其中行人流量代表了活力和建成环境的四个不同维度(即形态、形态、功能和景观)。研究发现：(1)白塔寺地区街道活力在时间上分布相对均匀，但具有较高的空间集中度；(2)小气候和建筑环境在冬季比夏秋季更显著；(3)街道形态和形态特征比街道功能和景观特征更能预测街道活力；(4)一般来说，兴趣点多样性较高、建筑较高、网络连接较强的街道往往具有较高的活力。这项研究为决策者在振兴历史街区方面提供了见解。
Vibrancy is indispensable and beneficial for revitalization of historic districts. Hence, identifying built environment predictors for vibrancy is of great interest to urban practitioners and policy makers. However, it is challenging. On the one hand, there is no consensus in selection of appropriate proxy for vibrancy. On the other hand, the built environment is multidimensional, but limited studies examined its impacts on vibrancy from different dimensions simultaneously. The Baitasi Area is a typical historic district in Beijing, China. In this study, on the basis of a long-term repeatedly measured dataset generated from the Citygrid sensors, we investigated the spatiotemporal distribution of street vibrancy in Baitasi Area and examined its built environment predictors in two seasons (i.e., summer/autumn and winter), with pedestrian volume as the proxy for vibrancy and built environment portrayed from four different dimensions (i.e., morphology, configuration, function, and landscape). We found that (1) the street vibrancy in Baitasi Area is temporally relatively evenly distributed, but with higher spatial concentration; (2) microclimate and built environment are more significant in winter than in summer/autumn; (3) street morphology and configuration features are more significant predictors than street function and landscape features; (4) generally, streets with higher point of interest (POI) diversity, higher buildings, and stronger network connection tend to have higher vibrancy. This study provides decision makers with insights in revitalizing historic districts.