A CiteSpace-Based Bibliometric Analysis of Artificial Intelligence in Urban Sustainable Design Research

As the process of sustainable urban development advances globally, green development has become a priority in urban renewal and development. The scientific analysis and management enabled by artificial intelligence can facilitate the rapid achievement of urban green development goals. As a result, a substantial amount of research is currently underway in this area. This paper provides a summary and analysis of the literature on urban green renewal driven by artificial intelligence from 2006 to 2024, aiming to identify current hot topics and future development trends. Using bibliometric methods and the CiteSpace software, a visual analysis was conducted on data from 5,421 selected articles, including information on countries, institutions, authors, keywords, and references. The results indicate that current research in this field primarily focuses on areas such as "machine learning," "green space," "urbanization," "dynamics," "air pollution," and "cloud computing." Additionally, this study presents potential future development trends in the field. The findings of this research will provide comprehensive insights into the current state of research and future directions for scholars in the field. Furthermore, the study can guide practitioners in exploring business opportunities and implementing best practices in the integration of artificial intelligence and urban green design innovation and technology applications. The research results can also offer valuable references for governments in formulating effective policies to guide the development of urban green renewal.