AI RESEARCH
From Street Form to Spatial Justice: Explaining Urban Exercise Inequality via a Triadic SHAP-Informed Framework
arXiv CS.LG
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ArXi:2507.03570v2 Announce Type: replace-cross Urban streets are essential everyday health infrastructure, yet their capacity to physical activity is unevenly distributed. This study develops a theory-informed and explainable framework to diagnose street-level exercise deprivation by integrating Lefebvre's spatial triad with multi-source urban data and SHAP-based analysis. Using Shenzhen as a, we show that while conceived spatial attributes have the strongest overall influence on exercise intensity, local deprivation mechanisms vary substantially across contexts.