邻里和街道层面的步行能力因素与步行行为有何关联?一种使用街景图像的大数据方法

IF 5.2 2区 心理学 Q1 ENVIRONMENTAL STUDIES Environment and Behavior Pub Date : 2021-05-17 DOI:10.1177/00139165211014609
B. Koo, S. Guhathakurta, Nisha Botchwey
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引用次数: 51

摘要

与可步行性相关的建筑环境特征包括从社区层面的城市形态因素到街道层面的城市设计因素。然而,现有的许多步行性指标都是基于社区层面的因素,缺乏对街道层面因素的考虑。可以说,这种遗漏是由于缺乏一种可扩展的方法来衡量它们。本文使用计算机视觉来量化美国乔治亚州亚特兰大市街景图像中的街道因素。相关分析表明,部分街景因素与社区层面因素高度相关。二元logistic回归表明,街道景观因素对步行方式选择的影响显著,街道景观因素对步行方式选择的影响大于社区因素。对这一结果的一种潜在解释是,基于图像的街景因素可以作为一些宏观因素的代理,同时代表从眼睛水平看到的行人体验。
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How are Neighborhood and Street-Level Walkability Factors Associated with Walking Behaviors? A Big Data Approach Using Street View Images
The built environment characteristics associated with walkability range from neighborhood-level urban form factors to street-level urban design factors. However, many existing walkability indices are based on neighborhood-level factors and lack consideration for street-level factors. Arguably, this omission is due to the lack of a scalable way to measure them. This paper uses computer vision to quantify street-level factors from street view images in Atlanta, Georgia, USA. Correlation analysis shows that some streetscape factors are highly correlated with neighborhood-level factors. Binary logistic regressions indicate that the streetscape factors can significantly contribute to explaining walking mode choice and that streetscape factors can have a greater association with walking mode choice than neighborhood-level factors. A potential explanation for the result is that the image-based streetscape factors may perform as proxies for some macroscale factors while representing the pedestrian experience as seen from eye-level.
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来源期刊
CiteScore
13.30
自引率
1.80%
发文量
13
期刊介绍: Environment & Behavior is an interdisciplinary journal designed to report rigorous experimental and theoretical work focusing on the influence of the physical environment on human behavior at the individual, group, and institutional levels.
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