Symbiotic Intelligence for Sustainable Cities: A Decadal Review of Generative AI, Ethical Algorithms, and Global South Innovations in Urban Green Space Research

作者：Tianrong Xu, Ainoriza Mohd Aini, Nikmatul Adha Nordin, Qi Shen, Liyan Huang, Wenbo Xu · 发表于：Buildings · 年份：2026 · DOI：10.3390/buildings16010231 · 研究领域：Urban Heat Island Mitigation、Building Energy and Comfort Optimization、Urban Green Space and Health

Urban Green Spaces (UGS) are integral components of the built environment, significantly contributing to its ecological, social, and performance dimensions, including microclimate regulation, occupant well-being, and energy efficiency. This decadal review (2015–2025) systematically analyzes 70 high-impact studies to propose a “Symbiotic Intelligence” framework. This framework integrates Generative AI, ethical algorithms, and innovations from the Global South to revolutionize the planning, design, and management of UGS within building landscapes and urban fabrics. Our analysis reveals that Generative AI can optimize participatory design processes and generate efficient planning schemes, increasing public satisfaction by 41% and achieving fivefold efficiency gains. Metaverse digital twins enable high-fidelity simulation of UGS performance with a mere 3.2% error rate, providing robust tools for building environment analysis. Ethical algorithms, employing fairness metrics and SHAP values, are pivotal for equitable resource distribution, having been shown to reduce UGS allocation disparities in low-income communities by 67%. Meanwhile, innovations from the Global South, such as lightweight federated learning and low-cost sensors, offer scalable solutions for building-environment monitoring under resource constraints, reducing model generalization error by 18% and decreasing data acquisition costs by 90%. However, persistent challenges-including data heterogeneity, algorithmic opac...