Research on the Spatial Heterogeneity of Urban Vitality Driven by Social Big Data: A Case Study of Xi’an

Based on multi-scale geographically weighted regression (MGWR) and spatial autocorrelation analysis, this paper explores the impact of different urban functional elements on urban vitality and their spatial heterogeneity. The results show that urban vitality exhibits significant spatial clustering within the study area, with both high and low values showing a clustered state. Scenic spots, business residences, and science, education, and culture facilities have a significant negative effect on urban vitality, while the positive effects of public facilities and life services are not significant. This suggests that the spatial layout and complexity of functional land use play an important role in urban vitality. The MGWR model significantly outperforms the traditional OLS model in terms of goodness of fit and explanatory power, indicating that considering spatial heterogeneity is crucial for revealing the formation mechanism of urban vitality. This study provides empirical reference and methodological support for urban spatial planning and functional layout optimization.