Data-Driven Intelligence for Sustainable Urban Renewal

Dear Colleagues,

Rapid urbanization, demographic shifts, and functional transitions have placed unprecedented pressure on many existing urban areas, which now face challenges such as aging infrastructure, inefficient land use, declining vitality, growing social disparities, and increasing environmental burdens. As a result, urban renewal has gradually shifted away from traditional “demolition–redevelopment” approaches toward more sustainable spatial restructuring, human-centered environment-making, and data-driven governance.

Meanwhile, advances in artificial intelligence (AI), sensing technologies, cloud computing, and spatial data infrastructures are profoundly transforming how cities identify problems, simulate interventions, and collaborate with communities to co-create future urban spaces. AI enables multi-source data fusion, automated spatial diagnostics, urban vitality prediction, generative design for urban form, and intelligent evaluation frameworks, supporting more precise, inclusive, and adaptive renewal strategies.

This Special Issue welcomes interdisciplinary research exploring how AI technologies—such as machine learning, computer vision, digital twins, generative design, and urban simulation—are reshaping the theories, methods, and practices of urban regeneration. We invite theoretical discussions, empirical analyses, technological innovations, and policy-oriented studies that investigate how AI can enhance the sustainability, resilience, and liveability of existing urban areas.

Areas of interest include, but are not limited to, the following topics:

• AI-based diagnosis of urban spatial problems and decline patterns;
• Machine learning for predicting urban vitality, mobility, and environmental performance;
• Multi-source urban data fusion (e.g., street view imagery, IoT sensors, remote sensing, socio-economic data);
• Digital twins and dynamic simulation for renewal strategies;
• Applications of generative AI in block redesign, public space renewal, and streetscape transformation;
• Intelligent evaluation tools for neighbourhood liveability, equity, and resilience;
• Data-supported co-creation and participatory community planning;
• AI-enabled conservation and adaptive reuse of historic or industrial districts;
• Ethical, social, and governance issues in AI-mediated urban renewal.

By bringing together researchers, practitioners, technologists, designers, and policymakers, this Special Issue seeks to advance a systematic understanding of how artificial intelligence can empower urban regeneration, enhance spatial quality, promote social equity, and support sustainable and human-centered urban futures.

Dr. Zhixing Li
Dr. Jing Dong
Dr. Yukai Zou
Dr. Zhiqiang Wang
Guest Editors

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