2023/05/20 by Kelsey Linnell, Linnell, Kelsey, Mikaela Irene Fudolig +13
Social Sciences · #Computers and Society (cs.CY) #FOS: Computer and information sciences #Human Mobility and Location-Based Analysis #Place Attachment and Urban Studies #Urban Transport and Accessibility
paper · pdf · doi:10.48550/arxiv.2305.12160
openalex publication_date 2023/05/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A large and growing body of research demonstrates the value of local parks to mental and physical well-being. Recently, researchers have begun using passive digital data sources to investigate equity in usage; exactly who is benefiting from parks? Early studies suggest that park visitation differs according to demographic features, and that the demographic composition of a park's surrounding neighborhood may be related to the utilization a park receives. Employing a data set of park visitations generated by observations of roughly 50 million mobile devices in the US in 2019, we assess the ability of the demographic composition of a park's walkshed to predict its yearly visitation. Predictive models are constructed using Support Vector Regression, LASSO, Elastic Net, and Random Forests. Surprisingly, our results suggest that the demographic composition of a park's walkshed demonstrates little to no utility for predicting visitation.