Polarization of urban vitality and density-related public health problems are major challenges facing modern cities. Against this backdrop, a study that empirically analyzed the complex phenomena of Korean cities using advanced data analytics and explainable machine learning has been published in international academic journals.

Won Dongrim, a PhD candidate in the Department of Urban Engineering at Jeonbuk National University (JBNU), together with his supervisor Professor Ji‑Wook Hwang, published two research papers as first author in the international urban planning journals Cities (IF=7.0, top 7% in JCR) and International Journal of Urban Sciences (IF=3.0), respectively.

Both studies are meaningful in that they used data-driven quantitative analyses to examine the spatial structure of urban vitality in Korea and the impact of urban density in metropolitan areas on public health risks, respectively.

The first study constructed an urban vitality index composed of six dimensions for 225 cities, counties, and districts nationwide and analyzed the spatial structure and interregional disparities of urban vitality in Korea. Based on the results, the research team defined Korea's urban vitality structure as “strong nodes–weak zones–broken corridors.”

The analysis found that high urban vitality is concentrated in major metropolitan centers, while surrounding areas have relatively low vitality, and continuous spatial corridors connecting high‑vitality areas are insufficiently formed. Accordingly, the study suggested the need for differentiated regional development and resource allocation policies tailored to city size and local characteristics.

In the second study, the researchers applied explainable machine learning and SHAP analysis to the Seoul and Busan metropolitan areas to analyze the nonlinear effects of urban density on health risks and the interactions among variables.

The analysis showed that household density and residential density are more important variables in explaining health risks than simple overall population density. The primary influencing factors and the threshold effects of density differed between the Seoul and Busan metropolitan areas. The study also confirmed that securing a certain level of open space within cities can help reduce various health risks.

These two studies are academically significant in that they empirically analyzed the imbalance of vitality across the national urban system and the issues of urban density and public health in metropolitan areas, respectively.

In particular, the studies are notable for applying data‑driven analytical methods such as spatial analysis and explainable machine learning to urban planning research, providing detailed analyses of the spatial characteristics of urban phenomena and inter‑variable relationships. The findings are expected to serve as baseline data for developing urban regeneration and balanced development policies tailored to regional characteristics, as well as health‑friendly urban planning.

PhD candidate Won Dongrim said, 'I am honored to have consecutive papers published as first author in international academic journals. I thank Professor Ji‑Wook Hwang for his generous guidance and advice, and I will continue research that contributes to solving practical urban problems through data analysis.'