Sangwan Lee
Biographic Data
| ID | 4418039 |
|---|---|
| NAME | Sangwan Lee |
| GIVEN NAMES | Sangwan |
| FAMILY NAME | Lee |
| SIGNATURE | LEE S |
| AFFILIATIONS | Korea Land and Geospatial Informatix Corporation, Jeollabuk-do, Republic of Korea |
| ORCID | 0000-0001-8039-6655 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 4 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Emerging megaregions and intensifying spatial polarization in South Korea
This study investigates the spatio-temporal evolution of spatial structure in South Korea, with the aim of understanding how spatial polarization and regional restructuring have unfolded over the past three decades. To achieve this, we apply Contour Tree Mapping and Emerging Hot Spot Analysis to Nighttime Light data. This study reveals three major findings. First, metropolitan areas such as Seoul and Busan continue to dominate the national urban …
Nonlinear and interaction effects of multi-dimensional street-level built environment features on urban vitality in Seoul
Multifaceted associations between built environments and POI visit patterns by trip purposes
Relationships between Transportation Expenditures and Built Environment in the United States
This study investigates the relationships between transportation expenditures and built environment (i.e., the D variables) in the United States using interpretable machine-learning (IML). Key findings include significant associations between these features, collectively contributing to 70.2 percent of feature importance. The study uncovers nonlinear relationships, such as transportation expenditures significantly declining after the compactness …
The Influence of Transportation Accessibility on Traffic Volumes in South Korea
This study explored how transportation accessibility and traffic volumes for automobiles, buses, and trucks are related. This study employed machine learning techniques, specifically the extreme gradient boosting decision tree model (XGB) and Shapley Values (SHAP), with national data sources in South Korea collected from the Korea Transport Institute, Statistics Korea, and National Spatial Data Infrastructure Portal. Several key findings of featu…
The Influence of Transportation Accessibility on Traffic Volumes in South Korea
This study explored how transportation accessibility and traffic volumes for automobiles, buses, and trucks are related. This study employed machine learning techniques, specifically the extreme gradient boosting decision tree model (XGB) and Shapley Values (SHAP), with national data sources in South Korea collected from the Korea Transport Institute, Statistics Korea, and National Spatial Data Infrastructure Portal. Several key findings of featu…
Relationships between Transportation Expenditures and Built Environment in the United States
This study investigates the relationships between transportation expenditures and built environment (i.e., the D variables) in the United States using interpretable machine-learning (IML). Key findings include significant associations between these features, collectively contributing to 70.2 percent of feature importance. The study uncovers nonlinear relationships, such as transportation expenditures significantly declining after the compactness …
Nonlinear and interaction effects of multi-dimensional street-level built environment features on urban vitality in Seoul
Multifaceted associations between built environments and POI visit patterns by trip purposes
Emerging megaregions and intensifying spatial polarization in South Korea
This study investigates the spatio-temporal evolution of spatial structure in South Korea, with the aim of understanding how spatial polarization and regional restructuring have unfolded over the past three decades. To achieve this, we apply Contour Tree Mapping and Emerging Hot Spot Analysis to Nighttime Light data. This study reveals three major findings. First, metropolitan areas such as Seoul and Busan continue to dominate the national urban …
Engineering (4 works) · Transport engineering (4 works) · Built environment (3 works) · Civil engineering (3 works) · Computer Science (2 works) · Geography (2 works) · Metropolitan area (2 works) · Transportation Planning and Optimization (2 works) · Urban Transport and Accessibility (2 works) · Architectural engineering (1 work)