TY - JOUR
T1 - Understanding changes in park visitation during the COVID-19 pandemic
T2 - A spatial application of big data
AU - Rice, William L.
AU - Pan, Bing
N1 - Publisher Copyright:
© 2021
PY - 2021/1
Y1 - 2021/1
N2 - 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.
AB - 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.
KW - Big data
KW - COVID-19
KW - Google
KW - Outdoor recreation
KW - Parks
KW - Spatial analysis
UR - http://www.scopus.com/inward/record.url?scp=85107687510&partnerID=8YFLogxK
U2 - 10.1016/j.wss.2021.100037
DO - 10.1016/j.wss.2021.100037
M3 - Article
AN - SCOPUS:85107687510
SN - 2666-5581
VL - 2
JO - Wellbeing, Space and Society
JF - Wellbeing, Space and Society
M1 - 100037
ER -