| Title |
AI-Driven Urban Design Research Trends: A Bibliometric Analysis (2015-2026) |
| Authors |
시이파 하나 아그리스티아(Agristya, Syifa Hana) ; 최보경(Choi, Bokyung) ; 정승현(Jung, Seunghyun) |
| DOI |
https://doi.org/10.38195/judik.2026.08.27.4.23 |
| Keywords |
도시설계; 인공지능; 사이언스 매핑; 서지계량분석 Urban Design; Artificial Intelligence; Science Mapping; Bibliometric Analysis |
| Abstract |
Urban design research has increasingly integrated artificial intelligence (AI) over the past decade, resulting in a rapid diversification of themes and methods; however, systematic analyses of its evolving thematic structure remain limited. This study analyzes 401 Web of Science publications on AI-driven urban design from 2015 to 2026 using science mapping, VOSviewer keyword co-occurrence analysis, density visualization, and temporal overlay mapping across three phases. The results show a nonlinear shift from exploratory applications to methodological convergence and diversification, with Digital Transformation of AI/ML rising from 26.0% to 52.1% of total keyword occurrences. However, the field remains strongly method-oriented, with relatively limited engagement with normative, social, and ethical dimensions. This study highlights the need to move beyond method adoption toward problem-oriented AI urbanism grounded in design purpose, interpretability, and accountability. |