Abstract

With social media platforms becoming popular in recent years, Big Data has become an effective way to explore human-oriented service capability of parks. In this research, the spatial accessibility of urban parks under four different travel modes (driving, transiting, biking, and walking) and multiple modes was analyzed by integrating the actual experiences of visitors and real travel time. We took the built-up area of Chengdu, Sichuan Province, China as the research area and drew conclusions as follows: 1) park accessibility of Chengdu still has a large space for promotion. 2) Residents living in the east region of Qingyang District and Wuhou District, north area of Jinniu District, and Chenghua District are more convenient to visit parks, as well as the population center of Longquanyi District, Shuangliu District, and Pidu District. In addition, riders and walkers are more likely to go to the nearest park. 3) Accessibility of parks would be affected significantly during peak hours and weekends by driving and multiple modes, while the other travel modes had little influence. 4) Spatial aggregation was more obvious during the peak hours of weekdays under driving modes, while there were obvious cold spot areas distributed continuously for riders. 5) Park desert was found in Yongquan Subdistrict, Jitouqiao Subdistrict, and Chenglonglu Subdistrict, which were near the downtown. Overall, Chengdu must make rational use of small and micro spaces in the city to add greenery to the corners of the city and integrate parks with other surrounding industries to inspire the entertainment, economy, and tourism function of parks. Through the modified 2SFCA method, this study provide a more realistic and human-oriented way to demonstrate the accessibility. Also, the results can guide cities to understand what reasonable and appropriate parks they need to build to achieve the equalization of park recreation services.

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