The COVID-19 pandemic has had a significant impact on urban mobility. While studies highlighted socioeconomic disparities, few have paid attention to the moderating role of the built environment in shaping those changes. To fill the gap, this paper investigates associations between the morphological features of the built environment and changes in population mobility patterns during the pandemic. We used SafeGraph’s travel data to Point of Interest (POI) sampled from 2019 to 2021 in Fulton County, Georgia to quantify mobility patterns at the census tract level. Through Principal Component Analysis and Factor Analysis, we extracted four key urban form features: density, connectivity, diversity, and centrality from a list of 12 raw built environment variables. Results of the spatial lag regression model indicate a significant relationship between the built environment and mobility changes, that a more diverse, denser, and more connected built environment can mitigate disparities of the mobility pattern changes which are often associated with inequitable socioeconomic backgrounds. And urban forms with higher density and diversity can encourage trips to green spaces, benefiting residents’ mental and physical health during the pandemic. This research enhances the understanding of the relationship between the built environment and population mobility patterns during the COVID-19 pandemic. These findings are useful for urban planning and public health, in which particular attention should be paid to suburban low-income neighborhoods as the most vulnerable group facing both socioeconomic and built environment disparities in public health crises. In addition, higher densities and mixed-use developments can also serve as effective strategies for urban planners and designers to strengthen urban mobility resilience in the future.

中文翻译：

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城市形态特征是否会延续大流行引发的流动性变化的差异？来自佐治亚州富尔顿县的证据

COVID-19 大流行对城市交通产生了重大影响。尽管研究强调了社会经济差异，但很少有人关注建筑环境在塑造这些变化中的调节作用。为了填补这一空白，本文研究了大流行期间建筑环境的形态特征与人口流动模式变化之间的关联。我们使用 SafeGraph 的旅行数据对佐治亚州富尔顿县 2019 年至 2021 年采样的兴趣点 (POI) 进行量化，以量化人口普查区层面的流动模式。通过主成分分析和因子分析，我们从 12 个原始建筑环境变量列表中提取了四个关键的城市形态特征：密度、连通性、多样性和中心性。空间滞后回归模型的结果表明，建筑环境与流动性变化之间存在显着关系，更多样化、更密集、联系更紧密的建筑环境可以减轻通常与不公平的社会经济背景相关的流动性模式变化的差异。更高密度和多样性的城市形态可以鼓励人们前往绿色空间，有利于疫情期间居民的身心健康。这项研究加深了人们对 COVID-19 大流行期间建筑环境与人口流动模式之间关系的理解。这些发现对于城市规划和公共卫生很有用，其中应特别关注郊区低收入社区，因为他们是在公共卫生危机中面临社会经济和建筑环境差异的最脆弱群体。此外，更高的密度和混合用途开发也可以作为城市规划者和设计师增强未来城市交通弹性的有效策略。