Publications
Chun, Y., Analyzing space-time crime incidents using eigenevector spatial filtering: An application to vehicle burglary, Geographical Analysis, (accepted). 2014 - Publication
Kim, H., Y. Chun, and K. Kim, Delimitation of functional regions using p-regions problem approach, International Regional Science Review, (in press), DOI: 10.1177/0160017613484929. 2014 - Publication
Griffith, D. A., Y. Chun, M. E. O'Kelly, B. J. L. Berry, R. P. Haining, and M.-P. Kwan, Geographical Analysis: Its first forty years, Geographical Analysis, 45(1), pp. 1-27. 2013 - Publication
Kim, Y., W. Zhong, and Y. Chun, Modeling Sanction Choices on Fraudulent Exchanges of Public Benefits, Journal of Artificial Societies and Social Simulation, 16(2), 8. 2013 - Publication
Kim, C., S. Sang, Y. Chun, and W. Lee, Exploring urban commuting imbalance by jobs and gender, Applied Geography, 32(2), pp. 532-545. 2012 - Publication
Chun, Y., H. Kim, and C. Kim, Modeling interregional commodity flows with incorporating network autocorrelation in spatial interaction models: An application of the U.S. interstate commodity flows, Computers, Environment and Urban Systems, (in press). 2012 - Publication
Chun, Y. and D. A. Griffith, On the quality of eigenvector spatial filtering based parameter estimates for the normal probability model: implications about uncertainty and specification error for georeferenced data, In Proceedings of the 10th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environment Sciences, pp. 1-6. 2012 - Publication
Chun, Y., Y. Kim, and H. Campbell, Using Bayesian Methods to Control for Spatial Autocorrelation in Environmental Justice Research: An Illustration Using Toxics Release Inventory Data for a Sunbelt County, Journal of Urban Affairs, (in press). 2012 - Publication
Chun, Y and D. Griffith, Modeling network autocorrelation in space-time migration flow data: An eigenvector spatial filtering approach, 101(3), pp. 523-536. 2011 - Publication
Qiu, F., H. Sridharan, and Y. Chun, Spatial autoregressive models for population estimation at the block level using LIDAR derived volume information, Cartography and Geographic Information Science, 37(3), pp. 239-257. 2010 - Publication
Appointments
Assistant Professor
The University of Texas at Dallas, Richardson [2009–Present]
Clinical Assistant Professor
The University of Texas at Dallas, Richardson [2008–2009]
Postdoctoral Research Fellow
The University of Texas at Dallas, Richardson [2007–2008]
Teaching/Research Assistant
The Ohio State University [2002–2007]
Academic Administration Assistant
Seoul National University [2001–2002]
GIS Analyst/Engineer
ESRI Korea Inc. [1997–2001]
Projects
Population estimation from a three dimensional perspective
2010–2010 The 106th Annual Meeting of the Association of American Geographers, Washington, DC, April 16 (Sridharan, Qiu, and Chun)
Network autocorrelation in migration flows
2008–2008 Department of Geography and Planning, The University of Akron, Akron, OH, February 22.
Modeling network autocorrelation among migration flows by spatial eigenvector filtering
2007–2007 The 103rd Annual Meeting of the Association of American Geographers, San Francisco, California, April 21.
An examination of network autocorrelation on urban traffic volume
2009–2009 The 105th Annual Meeting of the Association of American Geographers, Las Vegas, Nevada, March 25 (Kim, C. and Y. Chun).
Analyzing Spatial Data with R
2007–2007 (by Bivand), A workshop at the 103rd Annual Meeting of the Association of American Geographer, San Fanciscro, California, April 17 (Lab assistant).
News Articles

Two researchers in UT Dallas’
School of Economics, Political and Policy Sciences will explore uncertainty in spatial data with a grant awarded by the
National Institutes of Health.
The project focuses on documenting, visualizing and utilizing data error and uncertainty information in spatial analysis, said
Dr. Daniel A. Griffith, Ashbel Smith Professor of geospatial information sciences (GIS) and the principal investigator.
Dr. Yongwan Chun, an assistant professor of
GIS, will serve as co-investigator on the project.

Two researchers in UT Dallas’
School of Economics, Political and Policy Sciences will explore uncertainty in spatial data with a grant awarded by the
National Institutes of Health.
The project focuses on documenting, visualizing and utilizing data error and uncertainty information in spatial analysis, said
Dr. Daniel A. Griffith, Ashbel Smith Professor of geospatial information sciences (GIS) and the principal investigator.
Dr. Yongwan Chun, an assistant professor of
GIS, will serve as co-investigator on the project.

By applying a new method to modeling spatial patterns of crime, University of Texas at Dallas researcher
Dr. Yongwan Chunanalyzed vehicle burglaries in Plano, Texas, and found factors associated with increased and decreased burglary rates.
Chun, an assistant professor of
geospatial information sciences (GIS) in the
School of Economic, Political and Policy Sciences, used GIS data from the Plano Police Department to analyze the 17,549 vehicle burglaries that occurred from 2004 to 2009 in the Dallas suburb.
The method Chun applied is an extension of eigenvector spatial filtering (ESF), which was originally developed by two UT Dallas GIS faculty members,
Dr. Daniel Griffith and
Dr. Michael Tiefelsdorf. Chun’s study was published online in
Geographical Analysis in April.

By applying a new method to modeling spatial patterns of crime, University of Texas at Dallas researcher
Dr. Yongwan Chunanalyzed vehicle burglaries in Plano, Texas, and found factors associated with increased and decreased burglary rates.
Chun, an assistant professor of
geospatial information sciences (GIS) in the
School of Economic, Political and Policy Sciences, used GIS data from the Plano Police Department to analyze the 17,549 vehicle burglaries that occurred from 2004 to 2009 in the Dallas suburb.
The method Chun applied is an extension of eigenvector spatial filtering (ESF), which was originally developed by two UT Dallas GIS faculty members,
Dr. Daniel Griffith and
Dr. Michael Tiefelsdorf. Chun’s study was published online in
Geographical Analysis in April.