Assessing urban residents’ exposure to greenspace in daily travel from a dockless bike-sharing lens

Abstract

Considering the importance of greenspace for the health and life of urban citizens, different levels of greenspace exposure (GE) have received increasing attention. However, the understanding of human travel-related greenspace exposure is still limited, especially the lack of quantitative description of the fine-grained dynamics of greenspace exposure for active travel. Therefore, this study aims to quantify and analyse the spatio-temporal dynamics and equality of greenspace exposure during daily travel using dockless bike-sharing data in Beijing. Firstly, this study analysed the spatio-temporal patterns and community structure of bike-sharing travel using graph networks. Second, the daily travel-related greenspace exposure dynamics were estimated using a population-weighted exposure model. Finally, the spatial heterogeneity and equality of greenspace exposure during daily travel were assessed. The results show that greenspace exposure is shaped by both human mobility and greenspace distribution. Greenspace exposure is higher during the daytime than the early morning, and there are no significant changes of the average greenspace exposure across weekdays and weekends. In addition, there is an imbalance between greenspace coverage and exposure, with high greenspace coverage not implying high greenspace exposure and vice versa. Areas with lower greenspace coverage (less than 30 %) occurred for more than 80 % of the travels. We also found significant inequality of greenspace exposure during daily travel, with an average Gini index above 0.50. Driven by human mobility, inequality varied over time, with the highest inequality occurring between midnight and early morning, when the Gini index is higher than 0.65. This study provides a detailed understanding of greenspace exposure in active travel modes and may offer valuable insights for urban greenspace planning and health-oriented mobility strategies.

Keywords

• Graph network
• Greenspace exposure
• Human mobility
• Spatial heterogeneity