Evaluation of Spatial Matching between Urban Green Space and Population: Dynamics Analysis of Winter Population Data in Xi’an

Abstract

From the perspective of city dynamics, the spatial matching relationships between urban green space (UGS) and population are of great significance to the construction of an eco-livable city. In this study, Xi’an was taken as an example based on the big data of Google images and a Baidu heat map. The spatial matching relationships between UGS and the population were explored by using the coupled coordination model through the service capability index and population density index. The results show that there is a higher coupling degree, a lower coordination degree, and a larger spatiotemporal heterogeneity in coordination type between UGS and population in Xi’an. The reason for this is that many factors including urban spatial structure, expansion mode, functional differentiation, distribution pattern of large-scale ruins and relic sites, and urban planning management and control each have significant impacts on the spatial matching between UGS and population. Therefore, for the dense urban habitat, it is necessary not only to consider the spatial differences of job-housing and urban location conditions but also to actively protect the existing UGS, improve its accessibility, and enhance its quality. The dynamic evaluation of spatial matching between UGS and population is based on big data, which can maximize the utility of UGS resources in the dense urban habitat and provide theoretical guidance for spatial optimization, planning, and design.