Investigating factors influencing park visit flows and duration using mobile phone signaling data.

Quantifying residents' utilization of parks and understanding the driving factors behind it are essential for optimizing parks and promoting human well-being. However, previous literature has generally neglected the systematic investigation of visit flows, duration, and their spatiotemporal disparities along with the differential influence of park environmental factors on such measures. We addressed the gaps by combining visit flows and duration analysis based on mobile phone signaling data from 152 urban parks in Chengdu, China. We classified the parks into four categories based on the disparity between visit flows and duration. Through the Spearman rank correlation and spatial regression models, we identified the critical factors influencing park visit flows and duration. The findings reveal that: (1) There is a significant spatiotemporal disparity between visit flows and duration. (2) The main factors affecting park visit behavior included park area, types of facilities, distance to the city center, and the number of surrounding residents. (3) The regression models better explained visit flows than visit duration. (4) Environmental factors had a greater impact on park visit behaviors during weekends and peak hours. Selecting multi-dimensional indicators to quantify the use of urban parks provides valuable references for urban planners to optimize the urban park system. • Visit flows and duration of different parks have spatiotemporal disparities. • Low- and high-quality parks are identified by combining the two visit behaviors. • Park area, amenities, location, and nearby residents mainly affect park visits. • Regression models explain park visit flows better than park visit duration. • Influencing factors increasingly impact on visit behaviors at weekends and peaks. [ABSTRACT FROM AUTHOR]