The Causal Effect of Land-Use Transformation on Urban Vitality in the Context of Urban Regeneration: A Case Study of Chengdu

With the global deceleration of urbanization, traditional regeneration strategies centered on demolition and reconstruction have revealed substantial limitations. Against this backdrop, land-use transformation has emerged as a more cost-effective and less disruptive alternative. Focusing on Chengdu, China, this study employs a causal machine learning framework to rigorously assess the impacts of residential-to-commercial and industrial-to-commercial conversions on urban vitality. The findings demonstrate that population density consistently constitutes the fundamental driver across both transformation pathways. Residential-to-commercial conversion reflects a regeneration trajectory that integrates residential and commercial functions while prioritizing community livability, whereas industrial-to-commercial conversion entails large-scale spatial restructuring and enhanced accessibility. Overall, the study uncovers the heterogeneous causal effects of land-use transformation on urban vitality, thereby providing a theoretical basis to inform differentiated and sustainable urban regeneration policies.