Residential spatial differentiation and influencing factors of permanent and temporary populations based on mobile signaling data: A case study of Wuhan, China

Abstract

Understanding the residential spatial patterns of new migrants within urban environments is vital for addressing challenges related to urban governance, resource allocation, and formulating effective urban planning strategies. However, much of the existing literature focuses on macro-level analyses, often overlooking the nuanced distinctions and comparisons between permanent residential and immigration populations within cities. This study leverages nationwide mobile signaling data to differentiate between permanent population and temporary population in Wuhan, China. It constructs a comprehensive index that spans multiple dimensions, including science and education facilities, public transportation facilities, sports and leisure facilities, medical resources, and housing. The findings reveal that the spatial distribution of temporary population is predominantly shaped by factors such as science and education facilities, public transportation systems, and sports and leisure facilities, while permanent residents emphasize public transportation systems, medical resources, and housing. The geographically weighted regression (GWR) model and Ordinary Least Squares (OLS) method are applied to refine this analysis further, addressing the limitations of prior studies in examining the intricate spatial patterns within urban areas. The insights derived from this research offer valuable theoretical support and practical guidance for enhancing the settlement planning of the immigration population, improving public service efficiency, and fostering more significant spatial equity within urban environments.