Understanding changes in park visitation during the COVID-19 pandemic: A spatial application of big data

William L. Rice, Bing Pan

Research output: Contribution to journalArticlepeer-review

55 Scopus citations

Abstract

In the spring of 2020, the COVID-19 pandemic changed the daily lives of people around the world. In an effort to quantify these changes, Google released an open-source dataset pertaining to regional mobility trends—including park visitation trends. Changes in park visitation are calculated from an earlier baseline period for measurement. Park visitation is robustly linked to positive wellbeing indicators across the lifespan, and has been shown to support wellbeing during the COVID-19 pandemic. Therefore, this dataset offers vast application potential, containing aggregated information from location data collected via smartphones worldwide. However, empirical analysis of these data is limited. Namely, the factors influencing reported changes in mobility and the degree to which these changes can be directly attributable to COVID-19 remain unknown. This study aims to address these gaps in our understanding of the changes in park visitation, the causes of these changes (e.g., safer-at-home orders, amount of COVID-19 cases per county, climate, etc.) and possible impacts to wellbeing by constructing and testing a spatial regression model. Results suggest that elevation and latitude serve as primary influences of reported changes in park visitation from the baseline period. Therefore, it is surmised that Google's reported changes in park-related mobility are only partially the function of COVID-19.

Original languageEnglish (US)
Article number100037
JournalWellbeing, Space and Society
Volume2
DOIs
StatePublished - Jan 2021

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Health(social science)
  • Social Sciences (miscellaneous)

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