Urban renewal in high-density urban areas from the perspective of crowd psychological health

Accelerated urbanization intensifies urban density and mental well-being challenges, underscoring the need for integrated urban renewal strategies. This study proposes a multi-objective optimization method for early-stage renewal planning, using GIS for building data extraction and defining thermal radiation, UTCI, and psychological emotion as core objectives. Data were preprocessed via linear regression, with 3D/2D-Isovist quantifying emotion, and the NSGA-II algorithm generated Pareto-optimal solutions for building height adjustments. Results revealed antagonistic effects among objectives, with the mean optimal solution yielding minimal emotion improvement (0.0012%) but significant thermal radiation reduction (13.95%) and UTCI optimization (0.24%). This computational approach supports adaptable preliminary design balancing in diverse urban environments.