A Digital Twin-Enabled Framework for Sustainable Regeneration of Cold-Region Industrial Heritage: A Case Study of Harbin China

The sustainable regeneration of industrial heritage in cold regions is constrained by severe winter climate, seasonal behavioral shifts, and declining spatial vitality. However, existing research has rarely explained how cold-climate conditions influence catalyst effects and regeneration performance in industrial heritage areas. This study proposes a digital twin-enabled framework for the sustainable regeneration of cold-region industrial heritage. Using industrial heritage sites in Harbin, China, as a case study, the research integrates multi-source data to construct a dynamic assessment system that links climate constraints, spatial structure, and human activity patterns. The results show that winter conditions significantly reduce the effectiveness of traditional catalyst mechanisms by weakening outdoor interaction, fragmenting movement continuity, and increasing reliance on indoor transitional spaces. Simulation results further demonstrate that climate-responsive interventions, such as indoor connectivity enhancement, mixed-use functional implantation, and seasonal activity optimization, can improve regeneration effectiveness and spatial resilience. By combining digital twin technology with sustainable urban regeneration theory, this study provides a replicable analytical framework and practical decision-support tool for industrial heritage revitalization in cold-region cities.