Inequity in urban walking resources has been garnering increasing scholarly attention. However, there is still no widely accepted tool for assessing walkability, making results difficult to compare across studies. In addition, the ways in which walkability equity is typically defined and measured often overlook China’s local context. Therefore, this study develops a comprehensive walkability evaluation framework for Kunming’s main urban area using open-source data and census information, synthesizing 15 indicators across five dimensions (connectivity, accessibility, suitability, sociability, and aesthetics) analyzed through the Catastrophe Theory models (CT models). Furthermore, spatial autocorrelation, the Concentration Index (CI), and an interpretable machine learning framework (Random Forest-SHAP) are employed to examine the relationships between community walkability disparities and socio-economic factors for a spatial justice assessment. The results show the following: (1) Community walkability in the main urban area of Kunming exhibits a “core–periphery” spatial distribution pattern, where connectivity, accessibility, and sociability follow the general pattern, while suitability and aesthetics display heterogeneous spatial distributions. (2) The social differentiation characteristics of community walkability in Kunming’s main urban area correlate significantly with age structure, hukou registration, and social status, but show limited association with ethnicity and economic status. These findings challenge Western-centric social differentiation paradigms and underscore the context-specific nature of walkability equity in China, thus providing new perspectives for the understanding of built environment justice in the context of Chinese cities.
Si-yu et al. (Mon,) studied this question.