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

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