Correlating urban spatial form and crowd spatiotemporal behavior: A case study of Lhasa, China

Abstract

Understanding crowd behavior aids policymaking to foster livability and sustainability in cities. Spatial forms of the built environment can influence the way people use urban areas, thus exploring the correlation between them is increasingly deemed a useful support to address new city development or existing neighborhood regeneration. The study goal is to investigate the dynamic relationship between urban spatial morphology and crowd's spatiotemporal behavior, exploiting the potential of multi-source big data collection and integration. Hierarchical clustering and geographic distribution measurement are used to this end, and geographically weighted regression models are used to test their dynamic relationship, adopting Lhasa, China, as test-bed site.

Findings show that in Lhasa both the intensity and fluctuation level of crowd activities follow the “core agglomeration to peripheral weakening” pattern in the spatial distribution. The spatial form index can explain a large portion of the spatial heterogeneity of crowd spatiotemporal behavior, showing minimal temporal variation but significant spatial variation. Building density, building height, functional density, and functional mix positively impact crowd behavior, while plot ratio exerts a negative effect. Outcomes of this methodology could be highly relevant to understand how people behave in cities according to spatial forms, and lesson-learned can be derived accordingly to act as strategic guidance in urban growth.