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Exploring the spatiotemporal characteristics of park visitors and the “push and pull” factors that shape this mobility is critical to designing and managing urban parks to meet the demands of rapid urbanization. In this paper, 56 parks in Shenzhen were studied in 2019. First, cell phone signaling data were used to extract information on visitors’ departure locations and destination parks. Second, the bivariate Moran’s I and bivariate local Moran’s I (BiLISA) methods were used to identify the statistical correlation between the factors of the built environment and the park recreation trips. Finally, linear regression models were constructed to quantify the factors influencing the attractiveness of the park. Our study showed the following: (1) Recreation visitors at large parks varied significantly among population subgroups. Compared with younger adults, teenagers and older adults traveled lower distances and made fewer trips, and in particular, older adults of different genders differed significantly in park participation. (2) Recreational trips in large parks were related to the functional layout of the built environment around their residence. In areas with rich urban functions (e.g., southern Shenzhen), trips to large parks for leisure are more aggregated. (3) The findings reinforce the evidence that remote sensing data for urban vegetation can be an effective factor in characterizing park attractiveness, but the explanatory power of different vegetation data varies widely. Our study integrated the complementary human activity and remote sensing data to provide a more comprehensive understanding of urban park use and preferences. This will be important for future park planning.

Exploring Park Visit Variability Using Cell Phone Data in Shenzhen, China