| Title |
Urban Green Space and Residents’ Mental Health |
| Authors |
동웨이단(Dong, Wei-dan) ; 이상준(Lee, Sang Jun) ; 김미선(Kim, Mi-Sun) |
| DOI |
https://doi.org/10.5659/JAIK.2026.42.5.271 |
| Keywords |
Urban green space; Mental Health; Research Trends; Knowledge-mapping analysis; Bibliometric analysis |
| Abstract |
With accelerating urbanization, the role of urban green space in relieving psychological stress and promoting emotional restoration has become
increasingly significant. Although research in this field has expanded rapidly, its themes remain fragmented and methodological approaches
diverse, calling for a systematic and quantitatively grounded overview. Drawing on a relatively large corpus of 790 articles indexed in the
Web of Science Core Collection between 2009 and 2025, this study applies an integrated framework of bibliometric analysis and
knowledge?mapping techniques (CiteSpace, VOSviewer) to identify research hotspots, map thematic evolution, and detect emerging frontiers in
studies on urban green space and mental health. The results reveal a steep increase in publication output after 2017 and a peak in 2024,
indicating a transition from an exploratory stage to a mature research phase. A pronounced core?journal concentration is observed, with the
top 10 journals accounting for nearly half of all publications and three outlets?Urban Forestry & Urban Greening, International Journal of
Environmental Research and Public Health, and Landscape and Urban Planning?emerging as the principal platforms in this field. Keyword
co?occurrence and clustering analyses highlight key themes such as residential greenness, restorative environments, built?environment attributes,
ecosystem services, and physical?activity pathways, while co?citation analysis shows a clear shift from early work grounded in environmental
psychology and restorative theories to studies focusing on green?space exposure, health outcomes, and mechanism?oriented empirical
validation. Since 2020, topics such as COVID?19, accessibility and equity, vulnerable or aging populations, and the use of big data and deep
learning for fine?scale exposure assessment have rapidly gained prominence, illustrating deeper integration between urban planning, public
health, and data science. By combining large?scale bibliometric evidence with knowledge?mapping of thematic and intellectual structures, this
study offers an up?to?date and systematic synthesis that provides theoretical and methodological support for advancing equitable,
health?oriented green?space planning. |