Exploring the relationship between the built environment and block vitality based on multi-source big data: an analysis in Shenzhen, China

Abstract

Improving the vitality of cities has long been considered an important goal of planning. However, people’s understanding of how complex and diverse built environment factors affect urban vitality is still limited. In recent years, the emergence of new data provides a new perspective for the study of urban vitality. In this article, the spatio-temporal variation of urban vitality was quantitatively measured by using Baidu heat map, and the influence of built environment factors on urban vitality is further analyzed by geographically weighted regression model. The analysis was conducted at the block level, taking into account differences between weekdays and weekends. The results show that Shenzhen presents a vitality pattern of three centers and two sub-centers, and the average vitality level of weekdays is higher than that of weekends. Distance to subway station, road density, residential density, land mixed use, and compactness have significant influence on block vitality, but the influence varies from block to block, showing strong spatial heterogeneity. Commercial facility density and floor space ratio show significance only on weekends and weekdays, respectively. The findings reveal that we need to take regional differences into consideration and develop more targeted urban planning policies to facilitate block vitality.