Transportation Geography
My major research interest is how regional economies spatially interact and they shape the global economic space. I am interested in the relationship between the global transportation system and regional economic growth, such as the role of hub ports in the global trade network.
I especially focus on the global-scale transportation data, such as disaggregated global trade shipping records and global flight data, to examine global economic interactions. I have studied the the economic inequality in the global urban hierarchy system and port regionalization of the global trade shipping system. I also take part in World Bank project, by analyzing port choices of South African trade shipping to evaluate the quality of landside transportation systems in South African countries.
My works on the international freight transportation received attention by receiving the Transportation Geography Outstanding Dissertation Award at 2022 AAG and 1st Place Award for Graduate-Student-Led Paper Competition at 2021 NARSC.
Related Works and Publications
- Jung, P. H., Thill, J.-C. and Galvis-Aponte L. 2022+. State Failure, Violence and Trade: Dangerous Trade Routes in Colombia. [Under Review]
**1st Place Winner of the Graduate Student Paper Competition, 2021 NARSC - Jung, P. H. and Thill, J.-C. 2022+. Global Shrinkage of Space and the Hub-and-spoke System in the Global Trade Network. [Under Review]
- Jung, P. H. and Kim, K.-M. 2022+. Urban Hierarchy and Convergence of Global Urban System. [Under Review]
- Jung, P. H. and Thill, J.-C. 2022. Sea-land Independence and Delimitation of Port Foreland-hinterland Structures in the International Transportation System. Journal of Transport Geography, 99, 103297.
- Jung, P. H., Kim, H., Lee, K.-S. and Song, Y. 2022+. Examining Day-to-Day Dynamic Transit Accessibility Using Functional Data Analysis Approach. Professional Geographers, In Print.
- Jung, P. H., Kashiha, M. & Thill, J.-C. 2018. Community Structures in Networks of Disaggregated Cargo Flows to Maritime Ports. In Information Fusion and Intelligent Geographic Information Systems (pp. 167-186). Springer, Cham.
Spatial Analysis and Modeling
Another dimension of my research is the methodology of spatial data analysis. I focus on spatial econometric methods to better explain complex spatial structure in various data types, including spatial flow, social media and small area neighborhood data.
I currently aim to develop spatial statistical tools with which we can better estimate spatial autocorrelation and regression coefficients even with highly uncertain small area data, like census-tract level ACS estimates. I am now combining error-in-variable models and empirical Bayes approach with spatial econometric models to enable to use affluent demographic profiles of ACS estimates and open new horizon of neighborhood research.
My recent development of HC-EB Global and Local Moran’s I can help geographers to better estimate spatial autocorrelation statistics with ACS estimates. I was awarded the 1st Place Award for GIScience Paper Competition at 2018 AAG and 1st Place Award for Graduate-Student-Led Paper Competition at 2018 NARSC, for its methodological contribution in GIScience and spatial econometrics.
Related Works and Publications
- Delmelle, E., Desjardins, M. R., Jung, P. H., Owusu, C., Lan, Y., Hohl, A. and Dony, C. 2022. Uncertainty in Geospatial health: Challenges and Opportunities Ahead. Annals of Epidemiology, 65, 15-30.
- Jung, P. H. & Song, J. 2021. Multivariate Neighborhood Trajectory Analysis: A Propose of Functional Data Analysis Approach. Geographical Analysis, Online First.
**3rd Place Winner of John Odland Award for SAM Paper Competition, 2020 AAG - Jung, P. H., Thill, J.-C. & Issel, M. 2019. Spatial Autocorrelation and Data Uncertainty in the American Community Survey: A Critique. International Journal of Geographical Information Science. 33(6), 1155-1175.
- Jung, P. H., Thill, J.-C. & Issel, M. 2019. Spatial Autocorrelation Statistics of Areal Prevalence Rates under High Uncertainty in Denominator Data. Geographical Analysis. 51(3), 354-380.
**1st Place Winner of the GIScience Paper Competition, 2018 AAG
**1st Place Winner of the Graduate Student Paper Competition, 2018 NARSC