Abstract

Regular visits to park green space offer remarkable benefits for the physical and mental health of urban residents. Achieving a comprehensive understanding of the utilization across the entire city is a prerequisite for improving the overall utilization rate of park green spaces. Traditional social survey methods are limited by their sample size and time-consuming nature, while methods based on geographic location big data are gaining momentum. This study focuses on Xuchang, a medium-sized city in China, and systematically analyzes the current state and influencing factors of park green space utilization by mining GPS trajectory big data from April 3 to 12, 2022. Results indicate that residents' choices of park green spaces are highly diverse. Approximately 20% of visitors on holidays and weekends, and about 25% of visitors on weekdays, prefer the park green space closest to their homes. Notably, the distance threshold for park green space visits on weekdays, weekends, and holidays is 3633, 3824, and 4127 m, respectively. These distances are significantly higher than the several hundred meters specified in planning documents or commonly used in accessibility analyses. For individuals who frequently visit park green spaces, distance is the most critical influencing factor. Conversely, for those who occasionally visit, distance is not the primary consideration. For individuals who rarely or never visit park green spaces, personal attitudes play an essential role. In comparison to weekdays, the number of visitors on holidays and weekends is larger, the travel distance is longer, and they are more inclined to choose larger parks. Visits are concentrated in the afternoon and evening, and weather changes remarkably affect park green space utilization. Importantly, no compensatory effect is observed between the frequency and duration of park green space visits. These findings hold important implications for urban planning, management, and the promotion of park green space utilization.

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