Jean-Claude Thill

Dr. Thill is an economic geographer whose research focuses on urban and regional transportation and mobility issues, processes of urbanization, and data-centric spatial modeling. His recent research focuses on modeling past urbanization trajectories of the Charlotte metropolitan area (land use transformation, local and regional drifts in neighborhood quality of life), livability, innovation and mobility in Charlotte, other US cities and in Chinese cities, and accessibility to public services. Dr. Thill is Director of Project MOSAIC, a social science research initiative of UNC Charlotte.

Degrees:

• Ph.D. in Geography, Université Catholique de Louvain, Belgium
• M.S. in Regional Science, Université Catholique de Louvain, Belgium
• B.S. in Geography, Université Catholique de Louvain, Belgium

Expertise:

• Sustainable Urbanization
• Transportation and Mobility Systems
• Geographic Information Science (GIS-T)
• Spatial Modeling
• Regional Science
• International Comparative Urbanization
• Trade
• Cities
• Globalization

Websites:

• https://pages.charlotte.edu/jean-claude-thill/

Papers:

• Delmelle, Elizabeth C., Yuhong Zhou, and Jean-Claude Thill. “Densification without Growth Management? Evidence from Local Land Development and Housing Trends in Charlotte, North Carolina, USA.” Sustainability 6.6 (2014): 3975-90. The analysis of development and housing trends in Mecklenburg County revealed that although the number of developments have steadily increased, the amount of land consumed by each parcel has decreased over the examined time period. This transition was due to the revitalization of the Urban Core and “Smart Growth” principles applied to high intensity suburban developments. The shift was not mandated by local governments but was a direct response to developers’ profit potential.

• Wang, Chunhua, Jean‐Claude Thill, and Ross K. Meentemeyer. “Estimating the demand for public open space: Evidence from North Carolina municipalities*.” Papers in Regional Science 91.1 (2012): 219-232. The research reveals that open space behaves like a normal good. The demand increases with growth in income and decreases when land prices rise. Also of note, is the fact that pleasant year-round weather can be substituted for open space. Cities with pleasant consistent weather can allocate and preserve less open space.

• Hwang, Sungsoon, and Jean-Claude Thill. “Delineating urban housing submarkets with fuzzy clustering.” Environment and Planning B: Planning and Design 36.5 (2009): 865-882. Fuzzy Clustering provides a more realistic delineation of sub-market boundaries, because neighborhoods traditionally do not end in a hard line but blend into their adjacent neighborhoods. Results show that stratified hedonic models(fuzzy clustering) predicts house prices better than market wide hedonic models(hard line). They improve the accuracy of model predictions by 34% over a market wide model.