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Dr. Christopher Post
Professor of Environmental Information Science
Forestry and Environmental Conservation Department
Office: 218 Lehotsky Hall
Phone: 864-656-6939
Email: cpost@clemson.edu
Vita: Download CV
Personal Website: http://cg.is
Educational Background
Ph.D. Environmental Information Science
Cornell University
M.S. Field Crop Science
Cornell University
B.A. Biology
Reed College
Courses Taught
FOR 4340/6340 GIS for Natural Resources
FOR 8160 Advanced GIS and Remote Sensing
FOR 4070 CI: Conservation Drones
Profile
Dr. Post is the leader of the Clemson Intelligent River(r) project and is an expert in Geographic Information Systems, Remote Sensing and Environmental Sensor Networks.
Research Interests
My research interests focus on the use of innovative technologies to answer important scientific questions relating to our natural and built world. Tools range from satellite and UAV based remote sensing to water and terrestrial sensor networks. Specific focus areas include water quality and quantity, urban and production forestry and agriculture production.
Publications
Bolick, M.M., Post, C.J., Naser, M.Z., Forghanparast, F., and E.A. Mikhailova. 2023. Evaluating urban stream flooding with machine learning, LiDAR, and 3D modeling. Water 15, 2581.
Bolick, M.M., Post, C.J., Naser, M., and E.A. Mikhailova. 2023. Comparison of machine learning algorthms to predict dissolved oxygen in an urban stream. Environ. Sci. Pollut. Res. https://doi.org/10.1007/s11356-023-27481-5
Mikhailova, E.A., Lin, L., Hao, Z., Zurqani, H.A., Post, C.J., Schlautman, M.A., Post, G.C., and G.B. Shepherd. 2023. Question of liability for emissions from land development in relation to New York State climate change plan. Climate 11(5), 109.
Mikhailova, E.A., Lin, L., Hao, Z., Zurqani, H.A., Post, C.J., Schlautman, M.A., Post, G.C., Shepherd, G.B., and S.J. Kolarik. 2023. Enhancing the definitions of climate-change loss and damage based on land conversion in Florida, U.S.A. Urban Sci. 7, 40.
Lin, L., Hao, Z., Post, C.J., and E.A. Mikhailova. 2023. Protection of coastal shelter forests using UAVs: individual tree and tree-height detection in Casuriana Equisetifolia L. forests. Forests 14, 233.
Links
Google ScholarResearchGate