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Dr. Jeffrey Allen

Theme 5 leader: Water and energy management, policy, and economics

South Carolina Water Resources Center
Associated Themes: 2, 4, 5

WEC Research Relevance

Developed a GIS-based database management and spatial modeling program to characterize sources and effects of natural parameters and anthropogenic impacts to coastal ecosystems.  The program has been used by state agencies as a monitoring tool for coastal development.

Worked with the Saluda-Reedy Watershed Consortium to develop a land use change prediction and economic modeling program that has been used in workshops with civic leaders in western SC to educate on the costs and benefits of land development.

Developed a process to determine spatial relationships of polluted streams to animal agriculture systems that was used as input to state regulations on confined animal feeding operations in SC.

Current Projects

Coming soon

Recent Publications

Lu, Kang Shou., John Morgan, and Jeffery Allen,  (2011). “A Neural Network for Modeling Multicategorical Parcel Use Change”. International Journal of Applied Geospatial Research, 2(3),  20-31, July-September, 2011.

Campbell, C.E., J.S. Allen and K.S. Lu (2009). “Modeling Growth and Predicting Future Developed Land in the Upstate of South Carolina”. Research report submitted to the Saluda-Reedy Watershed Consortium and Upstate Forever. Greenville, SC.

Lu, Kang S., John Morgan, Matthew Sedecki and Jeffery S. Allen,  (2008). “Parcel and Sub-Parcel Land Use Change in Coastal South Carolina”. Final report for the CIDEEP program of the SC Sea Grant Consortium , December, 2008.

Allen, J.S. and K.S. Lu (2006). “Predicting Trajectories of Urban Growth in the Coastal Southeast”. In Changing Land Use Patterns in the Coastal Zone: Managing Environmental Quality in Rapidly Developing Regions, G.S. Kleppel, M.R. DeVoe and M.V. Rawson (eds.) Springer Science and Business Media, LLC.  New York, New York.

Allen, J. S. and K. S. Lu (2003). “Modeling and prediction of future urban growth in the Charleston region of South Carolina: a GIS-based integrated approach”. Conservation Ecology 8(2): 2.