Elijah Ramsey , III, Ph.D.
Ph.D., Department of Geography, University of South Carolina
M.S., Geophysical Sciences, Georgia Institute of Technology
B.S., Chemistry, University of Oregon
Elijah Ramsey III is a principal investigator of terrestrial and coastal ocean remote sensing and image processing in the U. S. Geological Survey, Wetland and Aquatic Research Center, Lafayette, Louisiana. His applied research is focused on producing consistent biophysical information directly relevant to sustaining critical natural resources that support the well-being of human and wildlife populations. As part of that focus, his work integrates data from passive to active and optical to radar systems that advance the response and strategic monitoring of natural resources and the human populations and facilities that occupy these environments. Current applied research include building a strategic mapping and monitoring system based on the integration of optical and radar image data, mapping invasive species, detection and monitoring of the onset and progression of detrimental change, operational subcanopy flood mapping, and the use of polarimetric radar for detection of subcanopy oil occurrence and definition of canopy structure. He has been honored with awards from the European Conference on Synthetic Aperture Radar and American Society of Photogrammetric Engineering & Remote Sensing for Scientific Publications, including the Leica Geosystems Award for Best Scientific Paper in Remote Sensing. He served as an Associate Editor for Wetlands and the Journal of Coastal Research and is currently an Associate Editor on Wetlands Ecology and Management.
In addition to completing graduate studies at the Univesity of South Carolina, he was a Research Project Manager in the Departments of Geography and Civil Engineering. As a postdoctorate, he modeled light interaction with various mangrove canopies based on an implemented radiative transfer model and used those results to simulated broadband and highspectral resolution satellite sensor imaging. In addition, he constructed an integrated system of computer models and algorithms to detect, isolate, and link rainfall events to storm hydrographs and couple those data with unit hydrograph theory within an nonlinear optimization to determing time-to-peak and peak rate factors for individual watersheds.