Dubayah, Ralph

Bio

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.

 

Degrees

  • Geography, University of California, Berkeley - BA

  • Geography, University of California, Santa Barbara - MA

  • Geography, University of California, Santa Barbara - Ph.D

Areas of Interest

  • Remote sensing of ecosystem structure
  • terrestrial carbon balance
  • biodiversity
  • active remote sensing (lidar and radar)
  • spatial analysis and modeling
  • surface energy balance

Research Topics

  • Carbon, Vegetation Dynamics and Landscape-Scale Processes
  • Geospatial Information Science and Remote Sensing
  • Duncanson, L., Montesano, P., Neuenschwander, A. L., Zarringhalam, A., Thomas, N., Minor, D., ... & Dubayah, R. (2026). Global and boreal estimates of woody aboveground biomass for 2020: Filling GEDI'S northern data gap with ICESat-2 and harmonized Landsat Sentinel-2. Remote Sensing of Environment, 340, 115406.

  • de Conto, T., Armston, J., & Dubayah, R. (2026). Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping. Machine Learning: Earth, 2(1), 015002.

  • Bruening, J. M., May, P. B., Dubayah, R. O., Wertis, L., Quinn, C., Pederson, N., ... & Poulter, B. (2026). Baseline maps of US mature and old-growth forests for conservation and management. Environmental Research: Ecology, 5(1), 015010.

  • De Conto, T., J. Armston, and R.O. Dubayah. (2026). GEDI L4C Global Waveform Structural Complexity Index (WSCI) Fusion Product, Version 2. ORNL DAAC, Oak Ridge, Tennessee, USA.

  • Bruening, J. M., May, P. B., Dubayah, R. O., Wertis, L., Quinn, C., Pederson, N., ... & Poulter, B. (2026). Mature and Old-growth Forest Probability Maps for the Conterminous United States. ORNL DAAC, Oak Ridge, Tennessee, USA.

  • Gao, X., Reich, P. B., Vincent, J. R., Fagan, M. E., Chazdon, R. L., Fritz, S., ... & Wang, D. (2025). The importance of distinguishing between natural and managed tree cover gains in the moist tropics. Nature Communications, 16(1), 6092.

  • Powell, E., Dubayah, R., Tully, K., Laurent, K. S., Duncanson, L., & Fatoyinbo, L. (2025). Spaceborne Lidar Observations Reveal Impacts of Inundation on Coastal Forest Structure across the US Mid-Atlantic. Estuarine, Coastal and Shelf Science, 109372.

  • Pascual, A., May, P. B., Cárdenas-Martínez, A., Guerra-Hernández, J., Hunka, N., Bruening, J. M., ... & Dubayah, R. O. (2025). Calibration of GEDI footprint aboveground biomass models in Mediterranean forests with NFI plots: A comparison of approaches. Journal of Environmental Management, 375, 124313.

  • Duncanson, L., Hunka, N., Jucker, T., Armston, J., Harris, N., Fatoyinbo, L., ... & Goetz, S. J. (2025). Spatial resolution for forest carbon maps. Science, 387(6732), 370-371.

  • Qi, W., Armston, J., Choi, C., Stovall, A., Saarela, S., Pardini, M., ... & Dubayah, R. (2025). Mapping large-scale pantropical forest canopy height by integrating GEDI lidar and TanDEM-X InSAR data. Remote Sensing of Environment, 318, 114534.

  • Seo, E., Healey, S., Yang, Z., Dubayah, R., de Conto, T., & Armston, J. (2025). GEDI L4D Imputed Waveforms, Version 2. ORNL DAAC, Oak Ridge, Tennessee, USA.

  • May, P. B., Dubayah, R. O., Bruening, J. M., Gaines, G. C. (2025). GEDI-FIA Fusion: Training Lidar Models to Estimate Forest Attributes. ORNL DAAC, Oak Ridge, Tennessee, USA.

  • Hurtt, G. C., Ma, L., Lamb, R., Campbell, E., Dubayah, R. O., Hansen, M., ... & Tang, H. (2024). Beyond MRV: combining remote sensing and ecosystem modeling for geospatial monitoring and attribution of forest carbon fluxes over Maryland, USA. Environmental Research Letters, 19(12), 124058.

  • Hunka, N., Duncanson, L., Armston, J., Dubayah, R., Healey, S. P., Santoro, M., ... & Melo, J. (2024). Intergovernmental Panel on Climate Change (IPCC) Tier 1 forest biomass estimates from Earth Observation. Scientific Data, 11(1), 1127.

  • de Conto, T., Armston, J., & Dubayah, R. (2024). Characterizing the structural complexity of the Earth’s forests with spaceborne lidar. Nature Communications, 15(1), 8116.

  • Siqueira, P., Armston, J., Chapman, B., Christensen, A., Cushman, K. C., Das, A., ... & Saatchi, S. (2024). Ecosystem Science with NISAR: Final Preparations in The Pre-Launch Period. In IGARSS 2024-2024 IEEE International Geoscience and Remote Sensing Symposium (pp. 6628-6630). IEEE.

  • Powell, E., Dubayah, R., & Stovall, A. E. (2024). Characterizing low‐lying coastal upland forests to predict future landward marsh expansion. Ecosphere, 15(6), e4867.

  • May, P. B., Dubayah, R. O., Bruening, J. M., & Gaines III, G. C. (2024). Connecting spaceborne lidar with NFI networks: A method for improved estimation of forest structure and biomass. International Journal of Applied Earth Observation and Geoinformation, 129, 103797.

  • May, P. B., Finley, A. O., & Dubayah, R. O. (2024). A spatial mixture model for spaceborne lidar observations over mixed forest and non-forest land types. Journal of Agricultural, Biological and Environmental Statistics, 1-24.

  • Bruening, J. M., Dubayah, R. O., Pederson, N., Poulter, B. & Calle, L. (2024). Definition criteria determine the success of old-growth mapping. Ecological Indicators, 159, 111709.

  • Qin, Y., Xiao, X., Tang, H., Dubayah, R., Doughty, R., Liu, D., ... & Moore III, B. (2024). Annual maps of forest cover in the Brazilian Amazon from analyses of PALSAR and MODIS images. Earth System Science Data, 16(1), 321-336.

  • Hunka, N., Duncanson, L., Armston, J., Dubayah, R. O., Healey, S. P., Santoro, M., ... & Melo, J. (2024). Classification of global forests for IPCC aboveground biomass Tier 1 estimates, 2020. ORNL DAAC, Oak Ridge, Tennessee, USA.

  • De Conto, T., Armston, J., & Dubayah, R. O. (2024). GEDI L4C Footprint Level Waveform Structural Complexity Index, Version 2. ORNL DAAC, Oak Ridge, Tennessee, USA.

  • Duncanson, L., Liang, M., Leitold, V., Armston, J., Krishna Moorthy, S. M., Dubayah, R., et al. (2023). The effectiveness of global protected areas for climate change mitigation. Nature Communications, 14(1).

  • Hunka, N., Santoro, M., Armston, J., Dubayah, R., McRoberts, R. E., Næsset, E., ... & Duncanson, L. (2023). On the NASA GEDI and ESA CCI biomass maps: aligning for uptake in the UNFCCC global stocktake. Environmental Research Letters, 18(12), 124042.

  • Bullock, E. L., Healey, S. P., Yang, Z., Acosta, R., Villalba, H., Insfrán, K. P., ... & Dubayah, R. (2023). Estimating aboveground biomass density using hybrid statistical inference with GEDI lidar data and Paraguay’s national forest inventory. Environmental Research Letters.

  • Pascual, A., Guerra-Hernández, J., Armston, J., Minor, D. M., Duncanson, L. I., May, P. B., ... & Dubayah, R. (2023). Assessing the performance of NASA’s GEDI L4A footprint aboveground biomass density models using National Forest Inventory and airborne laser scanning data in Mediterranean forest ecosystems. Forest Ecology and Management, 538, 120975.

  • Cushman, K. C., Armston, J., Dubayah, R., Duncanson, L., Hancock, S., Janík, D., ... & Kellner, J. R. (2023). Impact of leaf phenology on estimates of aboveground biomass density in a deciduous broadleaf forest from simulated GEDI lidar. Environmental Research Letters, 18(6), 065009.

  • Ma, L., Hurtt, G., Tang, H., Lamb, R., Lister, A., Chini, L., ... & Shen, Q. (2023). Spatial heterogeneity of global forest aboveground carbon stocks and fluxes constrained by spaceborne lidar data and mechanistic modeling. Global Change Biology.

  • May, P., McConville, K., Moisen, G., Bruening, J., Dubayah, R. (2023). A spatially varying model for small area estimates of biomass density across the contiguous United States. Remote Sensing of Environment, 286, 113420.

  • Bruening, J., May, P., Armston, J., Dubayah, R. (2023). Precise and unbiased biomass estimation from GEDI data and the US Forest Inventory. Frontiers in Forests and Global Change, 6.

  • Choi, C., Cazcarra-Bes, V., Guliaev, R., Pardini, M., Papathanassiou, K. P., Qi, W., ... & Dubayah, R. (2023). Large Scale Forest Height Mapping by Combining TanDEM-X and GEDI Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

  • Dubayah, R., Wood, E. F., & Lavallée, D. (2023). Multiscaling analysis in distributed modeling and remote sensing: an application using soil moisture. In Scale in remote sensing and GIS (pp. 93-112). Routledge.

  • Armston, J., Dubayah, R. O., Healey, S. P., Yang, Z., Patterson, P. L., Saarela, S., ... & Bruening, J. (2023). GEDI L4B Country-level Summaries of Aboveground Biomass. ORNL DAAC, Oak Ridge, Tennessee, USA.

  • Ma, L., Hurtt, G. C., Tang, H., Lamb, R., Lister, A. J., Chini, L. P., ... & Shen, Q. (2023). Global Forest Aboveground Carbon Stocks and Fluxes from GEDI and ICESat-2, 2018-2021. ORNL DAAC, Oak Ridge, Tennessee, USA.

  • Goetz, S., Dubayah, R., & Duncanson, L. (2022). Revisiting the status of forest carbon stock changes in the context of the measurement and monitoring needs, capabilities and potential for addressing reduced emissions from deforestation and forest degradation. Environmental Research Letters, 17(11), 111003.

  • Dubayah, R., Armston, J., Healey, S. P., Bruening, J. M., Patterson, P. L., Kellner, J. R., ... & Luthcke, S. (2022). GEDI launches a new era of biomass inference from space. Environmental Research Letters, 17(9), 095001.

  • Powell, E. B., St Laurent, K. A., & Dubayah, R. (2022). Lidar-Imagery Fusion Reveals Rapid Coastal Forest Loss in Delaware Bay Consistent with Marsh Migration. Remote Sensing, 14(18), 4577.

  • Duncanson, L., Kellner, J. R., Armston, J., Dubayah, R., Minor, D. M., Hancock, S., et al. (2022). Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission. Remote Sensing of Environment, 270, 112845.

  • Lang, N., Kalischek, N., Armston, J., Schindler, K., Dubayah, R., & Wegner, J. D. (2022). Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles. Remote Sensing of Environment, 268, 112760.

  • Qin, Y., Xiao, X., Wigneron, J. P., Ciais, P., Canadell, J. G., Brandt, et al. (2022). Large loss and rapid recovery of vegetation cover and aboveground biomass over forest areas in Australia during 2019–2020. Remote Sensing of Environment, 278, 113087.

  • Saarela, S., Holm, S., Healey, S. P., Patterson, P. L., Yang, Z., Andersen, H. E., et al. (2022). Comparing frameworks for biomass prediction for the Global Ecosystem Dynamics Investigation. Remote Sensing of Environment, 278, 113074.

  • Rappaport, D., Fagan, B. Swain, A., Dubayah, R., Morton, D. (2022) Animal soundscapes reveal key markers of Amazon forest degradation from fire and logging. Proceedings of the National Academy of Sciences, 119(18), e2102878119

  • Marselis, S. M., Keil, P., Chase, J. M. & Dubayah, R. O. (2022) The use of GEDI canopy structure for explaining variation in tree species richness in natural forests. Environmental Research Letters, 17(4), 045003

  • Dubayah, R.O., Armston, J., Healey, S.P., Yang, Z., Patterson, P.L., Saarela, S., et al. (2022). GEDI L4B Gridded Aboveground Biomass Density, Version 2. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2017

  • Ma, L., Hurtt, G., Tang, H., Lamb, R., Campbell, E., Dubayah, R.O., et al. (2022) Forest Aboveground Biomass and Carbon Sequestration Potential, Northeastern USA. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1922

  • Bruening, J. M., Fischer, R., Bohn, F. J., Armston, J., Armstrong, A. H., Knapp, N., et al. (2021). Challenges to aboveground biomass prediction from waveform lidar. Environmental Research Letters, 16(12), 125013.

  • Ma, L., Hurtt, G., Tang, H., Lamb, R., Campbell, E., Dubayah, R., et al. (2021). High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA. Environmental Research Letters, 16(4), 045014.

  • Clark, D. B., Oberbauer, S. F., Clark, D. A., Ryan, M. G., & Dubayah, R. O. (2021). Physical structure and biological composition of canopies in tropical secondary and old-growth forests. PloS One, 16(8), e0256571.

  • Duncanson, L., Armston, J., Disney, M., Avitabile, V., Barbier, N., Calders, K., et al. (2021). Aboveground Woody Biomass Product Validation: Good Practices Protocol. Good Practices for Satellite Derived Land Product Validation.

  • Fatoyinbo, T., Armston, J., Simard, M., Saatchi, S., Denbina, M., Lavalle, M., et al. (2021). The NASA AfriSAR campaign: Airborne SAR and lidar measurements of tropical forest structure and biomass in support of current and future space missions. Remote Sensing of Environment, 264, 112533.

  • Lamb, R. L., Hurtt, G. C., Boudreau, T. J., Campbell, E., Carlo, E. A. S., Chu, H.-H., et al. (2021). Context and future directions for integrating forest carbon into sub-national climate mitigation planning in the RGGI region of the US. Environmental Research Letters, 16(6), 063001.

  • Lamb, R. L., Ma, L., Sahajpal, R., Edmonds, J., Hultman, N. E., Dubayah, R. O., et al. (2021). Geospatial assessment of the economic opportunity for reforestation in Maryland, USA. Environmental Research Letters, 16(8), 084012.

  • Potapov, P., Li, X., Hernandez-Serna, A., Tyukavina, A., Hansen, M. C., Kommareddy, A., et al. (2021). Mapping global forest canopy height through integration of GEDI and Landsat data. Remote Sensing of Environment, 253, 112165.

  • Qin, Y., Xiao, X., Wigneron, J.-P., Ciais, P., Canadell, J. G., Brandt, M., et al. (2021). Annual Maps of Forests in Australia from Analyses of Microwave and Optical Images with FAO Forest Definition. Journal of Remote Sensing, 2021.

  • Silva, C. A., Duncanson, L., Hancock, S., Neuenschwander, A., Thomas, N., Hofton, M., et al. (2021). Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping. Remote Sensing of Environment, 253, 112234.

  • Tang, H., Ma, L., Lister, A., O’Neill-Dunne, J., Lu, J., Lamb, R. L., et al. (2021). High-resolution forest carbon mapping for climate mitigation baselines over the RGGI region, USA. Environmental Research Letters, 16(3), 035011.

  • Tang, H., Ma, L, Lister, A.J., O'Neil-Dunne, J., Lu, J., Lamb, R., et al. (2021). LiDAR Derived Biomass, Canopy Height, and Cover for New England Region, USA, 2015. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1854

  • Dubayah, R.O., Armston, J., Kellner, J.R., Duncanson, L., Healey, S.P., Patterson P.L., Hancock, S., Tang, H., Bruening, J., Hofton, M.A., Blair, J.B., and Luthcke, S.B. (2021). GEDI L4A Footprint Level Aboveground Biomass Density, Version 2. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1986

  • Dubayah, R., Tang, H., Armston, J., Luthcke, S., Hofton, M., Blair, J. (2021). GEDI L2B Canopy Cover and Vertical Profile Metrics Data Global Footprint Level V002 [Data set]. NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/GEDI/GEDI02_B.002

  • Dubayah, R.O., S.B. Luthcke, T.J. Sabaka, J.B. Nicholas, S. Preaux, and M.A. Hofton. (2021). GEDI L3 Gridded Land Surface Metrics, Version 2. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1952

  • Burns, P., Clark, M., Salas, L., Hancock, S., Leland, D., Jantz, P., et al. (2020). Incorporating canopy structure from simulated GEDI lidar into bird species distribution models. Environmental Research Letters, 15(9), 095002.

  • Duncanson, L., Neuenschwander, A., Hancock, S., Thomas, N., Fatoyinbo, T., Simard, M., et al. (2020). Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California. Remote Sensing of Environment, 242, 111779.

  • Marselis, S. M., Abernethy, K., Alonso, A., Armston, J., Baker, T. R., Bastin, J.-F., et al. (2020). Evaluating the potential of full-waveform lidar for mapping pan-tropical tree species richness. Global Ecology and Biogeography, 29(10), 1799–1816.

  • O’Leary III, D., Inouye, D., Dubayah, R., Huang, C., & Hurtt, G. (2020). Snowmelt velocity predicts vegetation green-wave velocity in mountainous ecological systems of North America. International Journal of Applied Earth Observation and Geoinformation, 89, 102110.

  • O’Leary III, D. S., Hurtt, G., Dubayah, R., Huang, C., Inouye, D., Lamb, R., & Ma, L. (2020). The Ecological Velocity of Climate Change. University of Maryland, College Park.

  • Schneider, F. D., Ferraz, A., Hancock, S., Duncanson, L. I., Dubayah, R. O., Pavlick, R. P., & Schimel, D. S. (2020). Towards mapping the diversity of canopy structure from space with GEDI. Environmental Research Letters, 15(11), 115006.

  • Dubayah, R., Hofton, M., Blair, J., Armston, J., Tang, H., Luthcke, S. (2020). GEDI L2A Elevation and Height Metrics Data Global Footprint Level V001 [Data set]. NASA EOSDIS Land Processes DAAC. Accessed 2022-03-09 from https://doi.org/10.5067/GEDI/GEDI02_A.001

  • Dubayah, R., Luthcke, S., Blair, J., Hofton, M., Armston, J., Tang, H. (2020). GEDI L1B Geolocated Waveform Data Global Footprint Level V001 [Data set]. NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/GEDI/GEDI01_B.001

  • Armston, J., Tang, H., Hancock, S., Marselis, S., Duncanson, L., KELLNER, J., ... & Dubayah, R. O. (2020). AfriSAR: Gridded Forest Biomass and Canopy Metrics Derived from LVIS, Gabon, 2016. ORNL DAAC.

  • Duncanson, L., Dubayah, R. O., Armston, J., Liang, M., Arthur, A., & Minor, D. (2020). CMS: LiDAR Biomass Improved for High Biomass Forests, Sonoma County, CA, USA, 2013. ORNL DAAC, Oak Ridge, Tennessee, USA.

  • Pardini, M., Armston, J., Qi, W., Lee, S. K., Tello, M., Bes, V. C., et al. (2019). Early lessons on combining lidar and multi-baseline SAR measurements for forest structure characterization. Surveys in Geophysics, 40(4), 803–837.

  • Patterson, P. L., Healey, S. P., Ståhl, G., Saarela, S., Holm, S., Andersen, H.-E., et al. (2019). Statistical properties of hybrid estimators proposed for GEDI—NASA’s global ecosystem dynamics investigation. Environmental Research Letters, 14(6), 065007.

  • Qi, W., Saarela, S., Armston, J., Ståhl, G., & Dubayah, R. (2019). Forest biomass estimation over three distinct forest types using TanDEM-X InSAR data and simulated GEDI lidar data. Remote Sensing of Environment, 232, 111283.

  • Rödig, E., Knapp, N., Fischer, R., Bohn, F. J., Dubayah, R., Tang, H., & Huth, A. (2019). From small-scale forest structure to Amazon-wide carbon estimates. Nature Communications, 10(1), 1–7.

  • Tang, H., Song, X.-P., Zhao, F. A., Strahler, A. H., Schaaf, C. L., Goetz, S., et al. (2019). Definition and measurement of tree cover: A comparative analysis of field-, lidar-and landsat-based tree cover estimations in the Sierra national forests, USA. Agricultural and Forest Meteorology, 268, 258–268.

  • Dubayah, R., Blair, J. B., Goetz, S., Fatoyinbo, L., Hansen, M., Healey, S., ... & Silva, C. (2020). The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography. Science of remote sensing, 1, 100002.

  • Flanagan, S. A., Hurtt, G. C., Fisk, J. P., Sahajpal, R., Zhao, M., Dubayah, R., ... & Collatz, G. J. (2019). Potential transient response of terrestrial vegetation and carbon in northern North America from climate change. Climate, 7(9), 113.

  • Hancock, S., Armston, J., Hofton, M., Sun, X., Tang, H., Duncanson, L. I., ... & Dubayah, R. (2019). The GEDI simulator: A large‐footprint waveform lidar simulator for calibration and validation of spaceborne missions. Earth and Space Science, 6(2), 294-310.

  • Huang, W., Dolan, K., Swatantran, A., Johnson, K., Tang, H., O’Neil-Dunne, J., ... & Hurtt, G. (2019). High-resolution mapping of aboveground biomass for forest carbon monitoring system in the Tri-State region of Maryland, Pennsylvania and Delaware, USA. Environmental Research Letters, 14(9), 095002.

  • Hurtt, G., Zhao, M., Sahajpal, R., Armstrong, A., Birdsey, R., Campbell, E., ... & Tang, H. (2019). Beyond MRV: high-resolution forest carbon modeling for climate mitigation planning over Maryland, USA. Environmental Research Letters, 14(4), 045013.

  • Marselis, S. M., Tang, H., Armston, J., Abernethy, K., Alonso, A., Barbier, N., ... & Dubayah, R. (2019). Exploring the relation between remotely sensed vertical canopy structure and tree species diversity in Gabon. Environmental Research Letters, 14(9), 094013.

  • Pardini, M., Armston, J., Qi, W., Lee, S. K., Tello, M., Cazcarra Bes, V., ... & Fatoyinbo, L. E. (2019). Early lessons on combining lidar and multi-baseline SAR measurements for forest structure characterization. Surveys in Geophysics, 40, 803-837.

  • Patterson, P. L., Healey, S. P., Ståhl, G., Saarela, S., Holm, S., Andersen, H. E., ... & Yang, Z. (2019). Statistical properties of hybrid estimators proposed for GEDI—NASA’s global ecosystem dynamics investigation. Environmental Research Letters, 14(6), 065007.

  • Qi, W., Saarela, S., Armston, J., Ståhl, G., & Dubayah, R. (2019). Forest biomass estimation over three distinct forest types using TanDEM-X InSAR data and simulated GEDI lidar data. Remote Sensing of Environment, 232, 111283.

  • Qi, W., Lee, S. K., Hancock, S., Luthcke, S., Tang, H., Armston, J., & Dubayah, R. (2019). Improved forest height estimation by fusion of simulated GEDI Lidar data and TanDEM-X InSAR data. Remote Sensing of Environment, 221, 621-634.

  • Tang, H., Armston, J., Hancock, S., Marselis, S., Goetz, S., & Dubayah, R. (2019). Characterizing global forest canopy cover distribution using spaceborne lidar. Remote Sensing of Environment, 231, 111262.

  • Tang, H., Song, X. P., Zhao, F. A., Strahler, A. H., Schaaf, C. L., Goetz, S., ... & Dubayah, R. (2019). Definition and measurement of tree cover: A comparative analysis of field-, lidar-and landsat-based tree cover estimations in the Sierra national forests, USA. Agricultural and forest meteorology, 268, 258-268.

  • Hurtt, G., Zhao, M., Sahajpal, R., Armstrong, A., Birdsey, R., Campbell, E., ... & Tang, H. (2019). Forest Aboveground Biomass and Carbon Sequestration Potential for Maryland, USA. ORNL DAAC.

  • Duncanson, L., & Dubayah, R. (2018). Monitoring individual tree‐based change with airborne lidar. Ecology and evolution, 8(10), 5079-5089.

  • Marselis, S. M., Tang, H., Armston, J. D., Calders, K., Labrière, N., & Dubayah, R. (2018). Distinguishing vegetation types with airborne waveform lidar data in a tropical forest-savanna mosaic: A case study in Lopé National Park, Gabon. Remote Sensing of Environment, 216, 626-634.

  • Rappaport, D. I., Morton, D. C., Longo, M., Keller, M., Dubayah, R., & dos-Santos, M. N. (2018). Quantifying long-term changes in carbon stocks and forest structure from Amazon forest degradation. Environmental Research Letters, 13(6), 065013.

  • Urbazaev, M., Thiel, C., Cremer, F., Dubayah, R., Migliavacca, M., Reichstein, M., & Schmullius, C. (2018). Estimation of forest aboveground biomass and uncertainties by integration of field measurements, airborne LiDAR, and SAR and optical satellite data in Mexico. Carbon balance and management, 13, 1-20.

  • Dubayah, R. O., Swatantran, A., Huang, W., Duncanson, L., Johnson, K., Tang, H., ... & Hurtt, G. C. (2018). LiDAR Derived Biomass, Canopy Height and Cover for Tri-State (MD, PA, DE) Region, V2. ORNL DAAC.

  • Dolan, K. A., Hurtt, G. C., Flanagan, S. A., Fisk, J. P., Sahajpal, R., Huang, C., ... & Masek, J. G. (2017). Disturbance Distance: quantifying forests' vulnerability to disturbance under current and future conditions. Environmental Research Letters, 12(11), 114015.

  • Duncanson, L., Huang, W., Johnson, K., Swatantran, A., McRoberts, R. E., & Dubayah, R. (2017). Implications of allometric model selection for county-level biomass mapping. Carbon Balance and Management, 12, 1-11.

  • Huang, Q., Sauer, J. R., & Dubayah, R. O. (2017). Multidirectional abundance shifts among North American birds and the relative influence of multifaceted climate factors. Global Change Biology, 23(9), 3610-3622.

  • Huang, W., Swatantran, A., Duncanson, L., Johnson, K., Watkinson, D., Dolan, K., ... & Dubayah, R. (2017). County-scale biomass map comparison: a case study for Sonoma, California. Carbon Management, 8(5-6), 417-434.

  • Stavros, E. N., Schimel, D., Pavlick, R., Serbin, S., Swann, A., Duncanson, L., ... & Wennberg, P. (2017). ISS observations offer insights into plant function. Nature Ecology & Evolution, 1(7), 0194.

  • Tang, H., & Dubayah, R. (2017). Light-driven growth in Amazon evergreen forests explained by seasonal variations of vertical canopy structure. Proceedings of the National Academy of Sciences, 114(10), 2640-2644.

  • Dubayah, R. O., Swatantran, A., Huang, W., Duncanson, L., Tang, H., Johnson, K., ... & Hurtt, G. C. (2017). CMS: LiDAR-derived Biomass, Canopy Height and Cover, Sonoma County, California, 2013. ORNL DAAC, Oak Ridge, Tennessee, USA.

  • Brolly, M., Simard, M., Tang, H., Dubayah, R. O., & Fisk, J. P. (2016). A lidar-radar framework to assess the impact of vertical forest structure on interferometric coherence. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(12), 5830-5841.

  • Huang, Q., Sauer, J. R., Swatantran, A., & Dubayah, R. (2016). A centroid model of species distribution with applications to the Carolina wren Thryothorus ludovicianus and house finch Haemorhous mexicanus in the United States. Ecography, 39(1), 54-66.

  • Hurtt, G. C., Thomas, R. Q., Fisk, J. P., Dubayah, R. O., & Sheldon, S. L. (2016). The impact of fine-scale disturbances on the predictability of vegetation dynamics and carbon flux. PLoS One, 11(4), e0152883.

  • Montesano, P. M., Sun, G., Dubayah, R. O., & Ranson, K. J. (2016). Spaceborne potential for examining taiga–tundra ecotone form and vulnerability. Biogeosciences, 13(13), 3847-3861.

  • Qi, W., & Dubayah, R. O. (2016). Combining Tandem-X InSAR and simulated GEDI lidar observations for forest structure mapping. Remote sensing of Environment, 187, 253-266.

  • Swatantran, A., Tang, H., Barrett, T., DeCola, P., & Dubayah, R. (2016). Rapid, high-resolution forest structure and terrain mapping over large areas using single photon lidar. Scientific reports, 6(1), 28277.

  • Tang, H., Ganguly, S., Zhang, G., Hofton, M. A., Nelson, R. F., & Dubayah, R. (2016). Characterizing leaf area index (LAI) and vertical foliage profile (VFP) over the United States. Biogeosciences, 13(1), 239-252.

  • Tang, H., Swatantran, A., Barrett, T., DeCola, P., & Dubayah, R. (2016). Voxel-based spatial filtering method for canopy height retrieval from airborne single-photon lidar. Remote Sensing, 8(9), 771.

  • Basu, S., Ganguly, S., Nemani, R. R., Mukhopadhyay, S., Zhang, G., Milesi, C., ... & Li, S. (2015). A semiautomated probabilistic framework for tree-cover delineation from 1-m NAIP imagery using a high-performance computing architecture. IEEE Transactions on Geoscience and Remote Sensing, 53(10), 5690-5708.

  • Duncanson, L., Rourke, O., & Dubayah, R. (2015). Small sample sizes yield biased allometric equations in temperate forests. Scientific reports, 5(1), 17153.

  • Duncanson, L. I., Dubayah, R. O., Cook, B. D., Rosette, J., & Parker, G. (2015). The importance of spatial detail: Assessing the utility of individual crown information and scaling approaches for lidar-based biomass density estimation. Remote Sensing of Environment, 168, 102-112.

  • Duncanson, L. I., Dubayah, R. O., & Enquist, B. J. (2015). Assessing the general patterns of forest structure: quantifying tree and forest allometric scaling relationships in the U nited S tates. Global Ecology and Biogeography, 24(12), 1465-1475.

  • Huang, W., Swatantran, A., Johnson, K., Duncanson, L., Tang, H., O’Neil Dunne, J., ... & Dubayah, R. (2015). Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA. Carbon balance and management, 10, 1-16.

  • Huang, W., Sun, G., Ni, W., Zhang, Z., & Dubayah, R. (2015). Sensitivity of multi-source SAR backscatter to changes in forest aboveground biomass. Remote Sensing, 7(8), 9587-9609.

  • Johnson, K. D., Birdsey, R., Cole, J., Swatantran, A., O’Neil-Dunne, J., Dubayah, R., & Lister, A. (2015). Integrating LIDAR and forest inventories to fill the trees outside forests data gap. Environmental monitoring and assessment, 187, 1-8.

  • Montesano, P. M., Rosette, J., Sun, G., North, P., Nelson, R. F., Dubayah, R. O., ... & Kharuk, V. (2015). The uncertainty of biomass estimates from modeled ICESat-2 returns across a boreal forest gradient. Remote Sensing of Environment, 158, 95-109.

  • Tang, H., Ganguly, S., Zhang, G., Hofton, M. A., Nelson, R. F., & Dubayah, R. (2016). Characterizing leaf area index (LAI) and vertical foliage profile (VFP) over the United States. Biogeosciences, 13(1), 239-252.

  • Hurtt, G. C., Thomas, R. Q., Fisk, J., Dubayah, R. O., & Sheldon, S. L. (2016). Canopy Height and Biomass from LiDAR Surveys at La Selva, Costa Rica, 1998 and 2005. ORNL DAAC, Oak Ridge, Tennessee, USA.

  • Dubayah, R. O., Swatantran, A., Huang, W., Duncanson, L., Johnson, K., Tang, H., ... & Hurtt, G. C. (2016). CMS: LiDAR-derived Aboveground Biomass, Canopy Height and Cover for Maryland, 2011. ORNL DAAC, Oak Ridge, Tennessee, USA.

  • Duncanson, L. I., Cook, B. D., Hurtt, G. C., & Dubayah, R. O. (2014). An efficient, multi-layered crown delineation algorithm for mapping individual tree structure across multiple ecosystems. Remote Sensing of Environment, 154, 378-386.

  • Goetz, S. J., Sun, M., Zolkos, S., Hansen, A., & Dubayah, R. (2014). The relative importance of climate and vegetation properties on patterns of North American breeding bird species richness. Environmental Research Letters, 9(3), 034013.

  • Hansen, A. J., Phillips, L. B., Dubayah, R., Goetz, S., & Hofton, M. (2014). Regional-scale application of lidar: Variation in forest canopy structure across the southeastern US. Forest Ecology and Management, 329, 214-226.

  • Huang, Q., Swatantran, A., Dubayah, R., & Goetz, S. J. (2014). The influence of vegetation height heterogeneity on forest and woodland bird species richness across the United States. PLoS One, 9(8), e103236.

  • Johnson, K. D., Birdsey, R., Finley, A. O., Swantaran, A., Dubayah, R., Wayson, C., & Riemann, R. (2014). Integrating forest inventory and analysis data into a LIDAR-based carbon monitoring system. Carbon Balance and Management, 9, 1-11.

  • Montesano, P. M., Nelson, R. F., Dubayah, R. O., Sun, G., Cook, B. D., Ranson, K. J. R., ... & Kharuk, V. (2014). The uncertainty of biomass estimates from LiDAR and SAR across a boreal forest structure gradient. Remote sensing of Environment, 154, 398-407.

  • Montesano, P. M., Sun, G., Dubayah, R., & Ranson, K. J. (2014). The uncertainty of plot-scale forest height estimates from complementary spaceborne observations in the taiga-tundra ecotone. Remote Sensing, 6(10), 10070-10088.

  • Mueller, T., Dressler, G., Tucker, C. J., Pinzon, J. E., Leimgruber, P., Dubayah, R. O., ... & Fagan, W. F. (2014). Human land-use practices lead to global long-term increases in photosynthetic capacity. Remote Sensing, 6(6), 5717-5731.

  • Tang, H., Brolly, M., Zhao, F., Strahler, A. H., Schaaf, C. L., Ganguly, S., ... & Dubayah, R. (2014). Deriving and validating Leaf Area Index (LAI) at multiple spatial scales through lidar remote sensing: A case study in Sierra National Forest, CA. Remote Sensing of Environment, 143, 131-141.

  • Tang, H., Dubayah, R., Brolly, M., Ganguly, S., & Zhang, G. (2014). Large-scale retrieval of leaf area index and vertical foliage profile from the spaceborne waveform lidar (GLAS/ICESat). Remote Sensing of Environment, 154, 8-18.

  • Huang, W., Sun, G., Dubayah, R., Cook, B., Montesano, P., Ni, W., & Zhang, Z. (2013). Mapping biomass change after forest disturbance: Applying LiDAR footprint-derived models at key map scales. Remote Sensing of Environment, 134, 319-332.

  • Whitehurst, A. S., Swatantran, A., Blair, J. B., Hofton, M. A., & Dubayah, R. (2013). Characterization of canopy layering in forested ecosystems using full waveform lidar. Remote Sensing, 5(4), 2014-2036.

  • Yang, X., Strahler, A. H., Schaaf, C. B., Jupp, D. L., Yao, T., Zhao, F., ... & Ni-Meister, W. (2013). Three-dimensional forest reconstruction and structural parameter retrievals using a terrestrial full-waveform lidar instrument (Echidna®). Remote sensing of environment, 135, 36-51.

  • Zhao, F., Yang, X., Strahler, A. H., Schaaf, C. L., Yao, T., Wang, Z., ... & Dubayah, R. O. (2013). A comparison of foliage profiles in the Sierra National Forest obtained with a full-waveform under-canopy EVI lidar system with the foliage profiles obtained with an airborne full-waveform LVIS lidar system. Remote Sensing of Environment, 136, 330-341.

  • Zolkos, S. G., Goetz, S. J., & Dubayah, R. (2013). A meta-analysis of terrestrial aboveground biomass estimation using lidar remote sensing. Remote sensing of environment, 128, 289-298.

  • Saatchi, S., Rodriguez, E., Denning, A., & Dubayah, R. (2013). LBA-ECO LC-15 Aerodynamic Roughness Maps of Vegetation Canopies, Amazon Basin: 2000. ORNL DAAC.

  • Baccini, A. G. S. J., Goetz, S. J., Walker, W. S., Laporte, N. T., Sun, M., Sulla-Menashe, D., ... & Houghton, R. (2012). Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature climate change, 2(3), 182-185.

  • Castillo, M., Rivard, B., Sánchez-Azofeifa, A., Calvo-Alvarado, J., & Dubayah, R. (2012). LIDAR remote sensing for secondary Tropical Dry Forest identification. Remote sensing of environment, 121, 132-143.

  • Dubayah, R. (2012). County-scale carbon estimation in NASA’s carbon monitoring system. Biomass Carbon Storage.

  • Huang, W., Sun, G., Dubayah, R., Zhang, Z., & Ni, W. (2012, July). Mapping forest above-ground biomass and its changes from LVIS waveform data. In 2012 IEEE International Geoscience and Remote Sensing Symposium (pp. 6561-6564). IEEE.

  • Pinto, N., Simard, M., & Dubayah, R. (2012). Using InSAR coherence to map stand age in a boreal forest. Remote Sensing, 5(1), 42-56.

  • Simard, M., Hensley, S., Lavalle, M., Dubayah, R., Pinto, N., & Hofton, M. (2012). An empirical assessment of temporal decorrelation using the uninhabited aerial vehicle synthetic aperture radar over forested landscapes. Remote Sensing, 4(4), 975-986.

  • Swatantran, A., Dubayah, R., Goetz, S., Hofton, M., Betts, M. G., Sun, M., ... & Holmes, R. (2012). Mapping migratory bird prevalence using remote sensing data fusion. PloS one, 7(1), e28922.

  • Tang, H., Dubayah, R., Swatantran, A., Hofton, M., Sheldon, S., Clark, D. B., & Blair, B. (2012). Retrieval of vertical LAI profiles over tropical rain forests using waveform lidar at La Selva, Costa Rica. Remote Sensing of Environment, 124, 242-250.

  • Goetz, S., & Dubayah, R. (2011). Advances in remote sensing technology and implications for measuring and monitoring forest carbon stocks and change. Carbon Management, 2(3), 231-244.

  • Anderson, J. E., Ducey, M. J., Fast, A., Martin, M. E., Lepine, L., Smith, M. L., ... & Blair, J. B. (2011). Use of waveform LiDAR and hyperspectral sensors to assess selected spatial and structural patterns associated with recent and repeat disturbance and the abundance of sugar maple (Acer saccharum Marsh.) in a temperate mixed hardwood and conifer forest. Journal of Applied Remote Sensing, 5(1), 053504-053504.

  • Bergen, K. M., Goetz, S. J., Dubayah, R. O., Henebry, G. M., Hunsaker, C. T., Imhoff, M. L., ... & Radeloff, V. C. (2009). Remote sensing of vegetation 3‐D structure for biodiversity and habitat: Review and implications for lidar and radar spaceborne missions. Journal of Geophysical Research: Biogeosciences, 114(G2).

  • Castillo-Núñez, M., Sánchez-Azofeifa, G. A., Croitoru, A., Rivard, B., Calvo-Alvarado, J., & Dubayah, R. O. (2011). Delineation of secondary succession mechanisms for tropical dry forests using LiDAR. Remote Sensing of Environment, 115(9), 2217-2231.

  • Dolan, K. A., Hurtt, G. C., Chambers, J. Q., Dubayah, R. O., Frolking, S., & Masek, J. G. (2011). Using ICESat's Geoscience Laser Altimeter System (GLAS) to assess large-scale forest disturbance caused by hurricane Katrina. Remote Sensing of Environment, 115(1), 86-96.

  • Cook, B., Dubayah, R., Hall, F. G., Nelson, R., Randon, K., Strahler, A. H., ... & Griffith, P. (2011). NACP New England and Sierra National Forests Biophysical Measurements: 2008-2010. ORNL DAAC.

  • Strahler, A. H., Schaaf, C., Woodcock, C., Jupp, D., Culvenor, D., Newnham, G., ... & Yang, X. (2011). ECHIDNA Lidar Campaigns: Forest Canopy Imagery and Field Data, USA, 2007-2009. ORNL DAAC.

  • Dubayah, R. O., Sheldon, S. L., Clark, D. B., Hofton, M. A., Blair, J. B., Hurtt, G. C., & Chazdon, R. L. (2010). Estimation of tropical forest height and biomass dynamics using lidar remote sensing at La Selva, Costa Rica. Journal of Geophysical Research: Biogeosciences, 115(G2).

  • Hall, F. G., Bergen, K., Blair, J. B., Dubayah, R., Houghton, R., Hurtt, G., ... & Wickland, D. (2011). Characterizing 3D vegetation structure from space: Mission requirements. Remote Sensing of Environment, 115(11), 2753-2775.

  • Hurtt, G. C., Fisk, J., Thomas, R. Q., Dubayah, R., Moorcroft, P. R., & Shugart, H. H. (2010). Linking models and data on vegetation structure. Journal of Geophysical Research: Biogeosciences, 115(G2).

  • Morton, D. C., DeFries, R. S., Nagol, J., Souza Jr, C. M., Kasischke, E. S., Hurtt, G. C., & Dubayah, R. (2011). Mapping canopy damage from understory fires in Amazon forests using annual time series of Landsat and MODIS data. Remote Sensing of Environment, 115(7), 1706-1720.

  • Swatantran, A., Dubayah, R., Roberts, D., Hofton, M., & Blair, J. B. (2011). Mapping biomass and stress in the Sierra Nevada using lidar and hyperspectral data fusion. Remote Sensing of Environment, 115(11), 2917-2930.

  • Dubayah, R. O., Sheldon, S. L., Clark, D. B., Hofton, M. A., Blair, J. B., Hurtt, G. C., & Chazdon, R. L. (2010). Estimation of tropical forest height and biomass dynamics using lidar remote sensing at La Selva, Costa Rica. Journal of Geophysical Research: Biogeosciences, 115(G2).

  • Goetz, S. J., Steinberg, D., Betts, M. G., Holmes, R. T., Doran, P. J., Dubayah, R., & Hofton, M. (2010). Lidar remote sensing variables predict breeding habitat of a Neotropical migrant bird. Ecology, 91(6), 1569-1576.

  • Hurtt, G. C., Fisk, J., Thomas, R. Q., Dubayah, R., Moorcroft, P. R., & Shugart, H. H. (2010). Linking models and data on vegetation structure. Journal of Geophysical Research: Biogeosciences, 115(G2).

  • Bergen, K. M., Goetz, S. J., Dubayah, R. O., Henebry, G. M., Hunsaker, C. T., Imhoff, M. L., ... & Radeloff, V. C. (2009). Remote sensing of vegetation 3‐D structure for biodiversity and habitat: Review and implications for lidar and radar spaceborne missions. Journal of Geophysical Research: Biogeosciences, 114(G2).

  • Kenyi, L. W., Dubayah, R., Hofton, M., & Schardt, M. (2009). Comparative analysis of SRTM–NED vegetation canopy height to LIDAR‐derived vegetation canopy metrics. International Journal of Remote Sensing, 30(11), 2797-2811.

  • Anderson, J. E., Plourde, L. C., Martin, M. E., Braswell, B. H., Smith, M. L., Dubayah, R. O., ... & Blair, J. B. (2008). Integrating waveform lidar with hyperspectral imagery for inventory of a northern temperate forest. Remote Sensing of Environment, 112(4), 1856-1870.

  • Robin, J., Dubayah, R., Sparrow, E., & Levine, E. (2008). Monitoring start of season in Alaska with GLOBE, AVHRR, and MODIS data. Journal of Geophysical Research: Biogeosciences, 113(G1).

  • Thomas, R. Q., Hurtt, G. C., Dubayah, R., & Schilz, M. H. (2008). Using lidar data and a height-structured ecosystem model to estimate forest carbon stocks and fluxes over mountainous terrain. Canadian Journal of Remote Sensing, 34(sup2), S351-S363.

  • Goetz, S., Steinberg, D., Dubayah, R., & Blair, B. (2007). Laser remote sensing of canopy habitat heterogeneity as a predictor of bird species richness in an eastern temperate forest, USA. Remote Sensing of Environment, 108(3), 254-263.

  • Kenyi, L., Dubayah, R., Hofton, M., Blair, J. B., & Schardt, M. (2007, July). Comparison of SRTM-NED data to LIDAR derived canopy metrics. In 2007 IEEE International Geoscience and Remote Sensing Symposium (pp. 2825-2829). IEEE.

  • Reitsma, F., & Dubayah, R. (2007). Simulating watershed runoff with a new data model. Hydrological Processes: An International Journal, 21(18), 2447-2457.

  • Anderson, J., Martin, M. E., Smith, M. L., Dubayah, R. O., Hofton, M. A., Hyde, P., ... & Knox, R. G. (2006). The use of waveform lidar to measure northern temperate mixed conifer and deciduous forest structure in New Hampshire. Remote Sensing of Environment, 105(3), 248-261.

  • Hofton, M., Dubayah, R., Blair, J. B., & Rabine, D. (2006). Validation of SRTM elevations over vegetated and non-vegetated terrain using medium footprint lidar. Photogrammetric Engineering & Remote Sensing, 72(3), 279-285.

  • Hyde, P., Dubayah, R., Walker, W., Blair, J. B., Hofton, M., & Hunsaker, C. (2006). Mapping forest structure for wildlife habitat analysis using multi-sensor (LiDAR, SAR/InSAR, ETM+, Quickbird) synergy. Remote Sensing of Environment, 102(1-2), 63-73.

  • Dubayah, R., Peterson, B., Rhoads, J., & Dietrich, W. E. (2006). Characterizing forest canopy structure and ground topography using lidar. Encyclopedia of hydrological sciences.

  • Hese, S., Lucht, W., Schmullius, C., Barnsley, M., Dubayah, R., Knorr, D., ... & Schröter, K. (2005). Global biomass mapping for an improved understanding of the CO2 balance—the Earth observation mission Carbon-3D. Remote Sensing of Environment, 94(1), 94-104.

  • Hyde, P., Dubayah, R., Peterson, B., Blair, J. B., Hofton, M., Hunsaker, C., ... & Walker, W. (2005). Mapping forest structure for wildlife habitat analysis using waveform lidar: Validation of montane ecosystems. Remote sensing of environment, 96(3-4), 427-437.

  • Hurtt, G. C., Dubayah, R., Drake, J., Moorcroft, P. R., Pacala, S., & Fearon, M. (2004). Beyond potential vegetation: combining lidar remote sensing and a height-structured ecosystem model for improved estimates of carbon stocks and fluxes. Ecological Applications, 14(3), 873-883.

  • Drake, J. B., Knox, R. G., Dubayah, R. O., Clark, D. B., Condit, R., Blair, J. B., & Hofton, M. (2003). Above‐ground biomass estimation in closed canopy neotropical forests using lidar remote sensing: Factors affecting the generality of relationships.

  • Global ecology and biogeography, 12(2), 147-159.Kotchenova, S. Y., Shabanov, N. V., Knyazikhin, Y., Davis, A. B., Dubayah, R., & Myneni, R. B. (2003). Modeling Lidar waveforms with time‐dependent stochastic radiative transfer theory for remote estimations of forest structure. Journal of Geophysical Research: Atmospheres, 108(D15).

  • Kotchenova, S. Y., Shabanov, N. V., Knyazikhin, Y., Davis, A. B., Dubayah, R., & Myneni, R. B. (2003). Modeling Lidar waveforms with time‐dependent stochastic radiative transfer theory for remote estimations of forest structure. Journal of Geophysical Research: Atmospheres, 108(D15).

  • Maurer, E. P., Rhoads, J. D., Dubayah, R. O., & Lettenmaier, D. P. (2003). Evaluation of the snow‐covered area data product from MODIS. Hydrological Processes, 17(1), 59-71.

  • Drake, J. B., Dubayah, R. O., Clark, D. B., Knox, R. G., Blair, J. B., Hofton, M. A., ... & Prince, S. (2002). Estimation of tropical forest structural characteristics using large-footprint lidar. Remote sensing of environment, 79(2-3), 305-319.

  • Drake, J. B., Dubayah, R. O., Knox, R. G., Clark, D. B., & Blair, J. B. (2002). Sensitivity of large-footprint lidar to canopy structure and biomass in a neotropical rainforest. Remote Sensing of Environment, 81(2-3), 378-392.

  • Hofton, M. A., Rocchio, L. E., Blair, J. B., & Dubayah, R. (2002). Validation of vegetation canopy lidar sub-canopy topography measurements for a dense tropical forest. Journal of geodynamics, 34(3-4), 491-502.

  • Lakshmi, V., Czajkowski, K., Dubayah, R., & Susskind, J. (2001). Land surface air temperature mapping using TOVS and AVHRR. International Journal of Remote Sensing, 22(4), 643-662.

  • Ni-Meister, W., Jupp, D. L., & Dubayah, R. (2001). Modeling lidar waveforms in heterogeneous and discrete canopies. IEEE transactions on geoscience and remote sensing, 39(9), 1943-1958.

  • Rhoads, J., Dubayah, R., Lettenmaier, D., O'Donnell, G., & Lakshmi, V. (2001). Validation of land surface models using satellite‐derived surface temperature. Journal of Geophysical Research: Atmospheres, 106(D17), 20085-20099.

  • Dubayah, R., Lettenmaier, D., Wood, E. F. & Rhoads, J. (2001). Using remote sensing data in macroscale hydrological modelling in Remote Sensing and Hydrology, M Owe, K Brubaker, J Ritchie and A Rango (editors) IAHS Publ. 267, IAHS Press, Wallingford, Oxon, UK. pp 151-155.

  • Crow, W. T., Wood, E. F., & Dubayah, R. (2000). Potential for downscaling soil moisture maps derived from spaceborne imaging radar data. Journal of Geophysical Research: Atmospheres, 105(D2), 2203-2212.

  • Dubayah, R. O., & Drake, J. B. (2000). Lidar remote sensing for forestry. Journal of forestry, 98(6), 44-46.

  • Dubayah, R. O., Wood, E. F., Engman, E. T., Czajkowski, K. P., Zion, M., & Rhoads, J. (2000). Remote sensing in hydrological modeling. Remote sensing in hydrology and water management, 85-102.

  • O'Donnell, G. M., Czajkowski, K. P., Dubayah, R. O., & Lettenmaier, D. P. (2000). Macroscale hydrological modeling using remotely sensed inputs: Application to the Ohio River basin. Journal of Geophysical Research: Atmospheres, 105(D10), 12499-12516.

  • Weishampel, J. F., Blair, J. B., Dubayah, R., Dubaya, R., Clark, D. B., & Knox, R. G. (2000). Canopy topography of an old-growth tropical rain forest landscape. Selbyana, 79-87.

  • Weishampel, J. F., Blair, J. B., Knox, R. G., Dubayah, R., & Clark, D. B. (2000). Volumetric lidar return patterns from an old-growth tropical rainforest canopy. International Journal of Remote Sensing, 21(2), 409-415.

  • Dubayah, R., Wood, E.G., Zion, M., and Czajkowski, K. (2000). A remote sensing approach to macroscale hydrological modeling, in Remote Sensing in Hydrology and Water Management, edited by G. Schultz and E. Engman, pp. 85-102, Springer-Verlag, New York.Dubayah, R., Knox, R., Hofton, M., and Blair, B. (2000). Land surface characterization using lidar remote sensing, in Spatial Information for Land Use Management, edited by M. Hill and R. Aspinall, pp. 25-38, Gordon and Breach, Amsterdam.

  • Kalluri, S. N. V., Dubayah, R. O., Czajkowski, K. P., & Goetz, S. J. (1998). Reply [to “Comment on ‘Comparison of atmospheric correction models for thermal bands of the advanced very high resolution radiometer over FIFE’by SN Kalluri and RO Dubayah”]. Journal of Geophysical Research: Atmospheres, 103(D6), 6243-6244.

  • Prince, S. D., Goetz, S. J., Dubayah, R. O., Czajkowski, K. P., & Thawley, M. (1998). Inference of surface and air temperature, atmospheric precipitable water and vapor pressure deficit using Advanced Very High-Resolution Radiometer satellite observations: comparison with field observations. Journal of Hydrology, 212, 230-249.

  • Dana, G. L., Wharton, Jr., R.A., Dubayah, R. (1998). Solar radiation in the McMurdo Dry Valleys, Antarctica, in Ecosystem Dynamics in a Polar Desert: The McMurdo Dry Valleys, Antarctica, edited by J. Priscu, pp. 39-64, American Geophysical Union.

  • Cialella, A. T., Dubayah, R., Lawrence, W., & Levine, E. (1997). Predicting soil drainage class using remotely sensed and digital elevation data. Photogrammetric Engineering and Remote Sensing, 63(2), 171-177.

  • Czajkowski, K. P., Mulhern, T., Goward, S. N., Cihlar, J., Dubayah, R. O., & Prince, S. D. (1997). Biospheric environmental monitoring at BOREAS with AVHRR observations. Journal of Geophysical Research: Atmospheres, 102(D24), 29651-29662.

  • DeFries, R., Hansen, M., Steininger, M., Dubayah, R., Sohlberg, R., & Townshend, J. (1997). Subpixel forest cover in central Africa from multisensor, multitemporal data. Remote Sensing of Environment, 60(3), 228-246.

  • Dubayah, R., & Loechel, S. (1997). Modeling topographic solar radiation using GOES data. Journal of Applied Meteorology, 36(2), 141-154.

  • Kaminsky, K. Z., & Dubayah, R. (1997). Estimation of surface net radiation in the boreal forest and northern prairie from shortwave flux measurements. Journal of Geophysical Research: Atmospheres, 102(D24), 29707-29716.

  • Liang, S., Lewis, P., Dubayah, R., Qin, W., & Shirey, D. (1997). Topographic effects on surface bidirectional reflectance scaling. Chin Jo Rem Sens, 1, 82-93.

  • Dubayah, R., Wood, E., and Lavallée, D. (1997). Multiscaling analysis in distributed modeling and remote sensing: an application using soil moisture, in Scales in Remote Sensing and GIS, edited by D.A. Quatrocchi and M. F. Goodchild, pp. 93-112, CRC/Lewis Publishers, Boca Raton, Florida.

  • Dubayah, R., & Rich, P. M. (1996). GIS-based solar radiation modeling. GIS and environmental modeling: Progress and research issues, 129134.

  • Hansen, M., Dubayah, R., & DeFries, R. (1996). Classification trees: an alternative to traditional land cover classifiers. International journal of remote sensing, 17(5), 1075-1081.

  • Dubayah, R. and Rich, R. (1996). GIS-based Solar Radiation Modeling, in GIS and Environmental Modeling:  Progress and Research Issues, edited by M.F. Goodchild, L.T. Steyaert and B.O. Parks, pp. 129-134, GIS World Books, Fort Collins, Colorado.

  • Dubayah, R., & Rich, P. M. (1995). Topographic solar radiation models for GIS. International journal of geographical information systems, 9(4), 405-419.

  • Hall, F. G., & Sellers, P. J. (1995). First international satellite land surface climatology project (ISLSCP) field experiment (FIFE) in 1995. Journal of Geophysical Research: Atmospheres, 100(D12), 25383-25395.

  • Kalluri, S. N., & Dubayah, R. O. (1995). Comparison of atmospheric correction models for thermal bands of the advanced very high resolution radiometer over FIFE. Journal of Geophysical Research: Atmospheres, 100(D12), 25411-25418.

  • Dubayah, R. C. (1994). Modeling a solar radiation topoclimatology for the Rio Grande River Basin. Journal of Vegetation Science, 5(5), 627-640.

  • Michaelsen, J., Schimel, D. S., Friedl, M. A., Davis, F. W., & Dubayah, R. C. (1994). Regression tree analysis of satellite and terrain data to guide vegetation sampling and surveys. Journal of Vegetation Science, 5(5), 673-686.

  • Davis, F. W., Schimel, D. S., Friedl, M. A., Michaelsen, J. C., Kittel, T. G. F., Dubayah, R., & Dozier, J. (1992). Covariance of biophysical data with digital topographic and land use maps over the FIFE site. Journal of Geophysical Research: Atmospheres, 97(D17), 19009-19021.

  • Dubayah, R. (1992). Estimating net solar radiation using Landsat Thematic Mapper and digital elevation data. Water resources research, 28(9), 2469-2484.

  • Dubayah, R., & Van Katwijk, V. (1992). The topographic distribution of annual incoming solar radiation in the Rio Grande River Basin. Geophysical Research Letters, 19(22), 2231-2234.

  • Dubayah, R., Dozier, J., & Davis, F. W. (1990). Topographic distribution of clear‐sky radiation over the Konza Prairie, Kansas. Water Resources Research, 26(4), 679-690. 

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Personal Website(s)

Ralph Dubayah

Ralph Dubayah
Distinguished University Professor

| 4600 River Road, Suite 354 (send mail to 2181 LeFrak)

| dubayah@umd.edu

| (301) 405-4069