Published time: 18 May 2020
Authors: William Rice, Bing Pan
Keywords: Big data, coronavirus, COVID-19, recreation parks, park visitation, spatial analysis, spatial error model
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. This dataset offers vast application potential, containing aggregated information from location data collected via smartphones around the world. However, empirical analysis of these data is limited. Namely, the factors causing reported changes in mobility and the degree to which these changes can be directly attributable to COVID-19 remain unknown. The goal of this study is to address these gaps in our understanding of both the changes in park visitation and the causes of these changes. Results suggest that seasonality, not the COVID-19 pandemic, serves as the primary driver of reported changes in park visitation. Specifically, latitude-driven seasonal changes significantly influence visitation trends. Median age of a county is also a statistically significant driver.
Understanding drivers of change in park visitation during the COVID-19 pandemic A spatial application of Big data