Department of Geographical Sciences
Ralph Dubayah is Professor of Geographical Sciences at the University of Maryland, College Park. He received his B.A. in 1982 from the University of California, Berkeley, and his M.A. (1985) and Ph.D. (1990) degrees from the University of California, Santa Barbara. His main areas of interest are ecosystem characterization for carbon modeling, habitat and biodiversity studies, land surface energy and water balance modeling, spatial analysis and remote sensing science. A common goal of his research is to develop and apply emerging technologies of spatial data acquisition and analysis to address environmental issues at policy-relevant scales. He has been an investigator for numerous NASA projects, including two Interdisciplinary Science Investigations (IDS) on the use of remote sensing for hydrological and ecosystem modeling, and has recent awards as PI for NASA's Carbon Management System (CMS) and the ICESAT2 mission. He was also principal investigator (1997-2000) for the Vegetation Canopy Lidar (VCL), a NASA mission to measure the three-dimensional structure of the Earth’s forests for carbon assessments. He has served in various national and international organizations and has served as an Associate Editor for the Journal of Geophysical Research (Biogeosciences), is on the editorial board of Remote Sensing of Environment and Remote Sensing, and was the Co-Lead Author for the CEOS Strategy for Carbon Observations from Space (2014). He is currently the Science Definition Team Co-Leader for NASA’s NISAR mission and a Science Team member for CMS. He was recently chosen (2014) as PI for the Global Ecosystems Dynamics Investigation Lidar (GEDI) as part of NASA's Earth Ventures Instrument 2 (EVI-2) competition. GEDI is led by the University of Maryland, in collaboration with NASA Goddard Spaceflight Center, and will deploy a multibeam lidar instrument onboard the International Space Station to measure the forest vertical structure and biomass.
- Remote sensing of ecosystem structure
- terrestrial carbon balance
- active remote sensing (lidar and radar)
- spatial analysis and modeling
- surface energy balance