This research uses smartphone-based big data to explore how socioeconomic, built environment characteristics, and spatiotemporal factors influence neighborhood park use, with a specific focus on minority groups’ park visitation patterns. Panel data are collected through SafeGraph, and combined with GIS and American Community Survey data. We analyze 12,227 visitations from 1121 block groups to 30 neighborhood parks from September 2019 to August 2020 in Austin, Texas. Time-fixed-effect nested regression models are employed to control for unobserved time-related effects. Findings indicate a substantial increase in overall park use during the pandemic, with visiting frequencies up by 22 % and dwell time by 56 %. In contrast, minority groups, including seniors, children, blacks, unemployed, living alone, and recent movers, exhibited a decline in park visits. It also highlights visitors’ risk-averse behaviors during the pandemic, such as avoiding visiting parks during holiday weeks and avoiding using swimming pools. Before the pandemic, proximity held the utmost significance for park use; during the pandemic, park quality and facilities emerged as the primary factors influencing park utilization. This study suggests that park planning needs to improve neighborhood parks’ proximity, park facilities, and park safety to boost park use and foster inclusive park planning.

中文翻译：

---

为包容性公园规划提供信息：德克萨斯州奥斯汀基于智能手机大数据的邻里公园访问建模


这项研究使用基于智能手机的大数据来探索社会经济、建筑环境特征和时空因素如何影响社区公园的使用，特别关注少数群体的公园访问模式。面板数据通过 SafeGraph 收集，并与 GIS 和美国社区调查数据相结合。我们分析了 2019 年 9 月至 2020 年 8 月德克萨斯州奥斯汀 1121 个街区组对 30 个社区公园的 12,227 次访问。采用时间固定效应嵌套回归模型来控制未观察到的时间相关效应。调查结果表明，疫情期间公园的总体使用量大幅增加，参观频率增加了 22%，停留时间增加了 56%。相比之下，少数群体，包括老年人、儿童、黑人、失业者、独居者和最近搬家的人，公园参观次数有所下降。它还强调了游客在大流行期间的规避风险行为，例如避免在假期期间参观公园和避免使用游泳池。在大流行之前，邻近性对于公园的使用至关重要。疫情期间，公园质量和设施成为影响公园利用率的首要因素。这项研究表明，公园规划需要改善社区公园的邻近性、公园设施和公园安全，以提高公园的利用并促进包容性的公园规划。