Sheltering in place: unveiling how urban park characteristics shaped visiting patterns during the pandemic using machine learning
Dawon Oh , In Kwon Park
Computational Urban Science ›› 2025, Vol. 5 ›› Issue (1) : 29
Sheltering in place: unveiling how urban park characteristics shaped visiting patterns during the pandemic using machine learning
During the pandemic, urban parks have played an increasingly important role in promoting urban sustainability by providing outdoor leisure activities. While some parks have served as havens from social isolation, promoting outdoor activity and physical and mental health, others have experienced a decline in visitors. This study aims to classify urban parks based on their visiting patterns during the pandemic and identify the locational factors and design elements that contribute to their typology. By analyzing location-based big data from 425 parks in Seoul, South Korea, we utilized a multinomial logit model and K-shape clustering to explore how park characteristics are linked to clusters with different visiting patterns. The findings reveal that Children's Parks, District Parks, and parks with sports facilities and appropriate sizes tend to be classified as a type with significantly increased visits during the pandemic era.
COVID-19 / Urban parks / Park visitor behavior / Location-based big data / Time-series clustering / Medical and Health Sciences / Public Health and Health Services
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