Station-based average travel distance and its relationship with urban form and land use:an analysis of smart card data in Nanjing City, China

Few studies based on large sample data have examined mobility patterns from a travel distance perspective and investigated the potential influence of urban form and land use on people's daily travel distances. This paper provides additional empirical insights into spatiotemporal urban mobility patterns and their relationship with urban form and land use using station-based average travel distances (ATDs). Drawing on smart card data of the Nanjing metro system, land use data and open source points-of-interest (POIs) data, we apply exploratory spatial data and quantile regression analysis to examine distance patterns and explore the potential effects of urban form and land use calculated at different spatial scales (i.e. 800 m, 2 km and 5 km) on the ATDs. By comparing mobility patterns between weekdays and weekends and for different times of day, our findings highlight that ATDs are not uniformly nor randomly distributed in space. Positive spatial autocorrelation is found for different time segments. The results of OLS and quantile regression models show a positive and robust relationship between ATDs and distances to the city center (DCs). The models also prove that land use mix (especially measured at the 2 km and 5 km scale) significantly affects ATDs, supporting the importance of land use mix in decreasing daily travel distances. No significant relationship is found between ATDs and distances to the nearest subsidiary center (DSCs), while the employment/entertainment-residence balance has a marginal effect on ATDs at relatively large spatial scales (i.e. 2 km, 5 km). Consequently, with respect to reducing the ATDs, we recommend enhancing land use mix and reducing the imbalance between employment/entertainment and residence at larger spatial scales. Potential applications and future research directions are discussed. The findings in the present paper are helpful for guiding urban planning and policy making