| Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission L Duncanson, JR Kellner, J Armston, R Dubayah, DM Minor, S Hancock, ... Remote Sensing of Environment 270, 112845, 2022 | 146 | 2022 |
| GEDI launches a new era of biomass inference from space R Dubayah, J Armston, SP Healey, JM Bruening, PL Patterson, JR Kellner, ... Environmental Research Letters 17 (9), 095001, 2022 | 85 | 2022 |
| Spatiotemporal variability in the climate growth response of high elevation bristlecone pine in the White Mountains of California AG Bunn, MW Salzer, KJ Anchukaitis, JM Bruening, MK Hughes Geophysical Research Letters, 2018 | 38 | 2018 |
| Cluster analysis and topoclimate modeling to examine bristlecone pine tree-ring growth signals in the Great Basin, USA TJ Tran, JM Bruening, AG Bunn, MW Salzer, SB Weiss Environmental Research Letters 12 (1), 014007, 2017 | 26 | 2017 |
| Fine-scale modeling of bristlecone pine treeline position in the Great Basin, USA JM Bruening, TJ Tran, AG Bunn, SB Weiss, MW Salzer Environmental Research Letters 12 (1), 014008, 2017 | 24 | 2017 |
| Challenges to aboveground biomass prediction from waveform lidar JM Bruening, R Fischer, FJ Bohn, J Armston, AH Armstrong, N Knapp, ... Environmental Research Letters 16 (12), 125013, 2021 | 14 | 2021 |
| A climate‐driven tree line position model in the White Mountains of California over the past six millennia JM Bruening, AG Bunn, MW Salzer Journal of biogeography 45 (5), 1067-1076, 2018 | 11 | 2018 |
| A spatially varying model for small area estimates of biomass density across the contiguous United States P May, KS McConville, GG Moisen, J Bruening, R Dubayah Remote Sensing of Environment 286, 113420, 2023 | 8 | 2023 |
| GEDI L4A Footprint Level Aboveground Biomass Density R Dubayah, J Armston, J Kellner, L Duncanson, S Healey, P Patterson, ... Version, 2021 | 6 | 2021 |
| Fine-scale topoclimate modeling and climatic treeline prediction of Great Basin bristlecone pine (Pinus longaeva) in the American southwest JM Bruening Western Washington University, 2016 | 6 | 2016 |
| Precise and Unbiased Biomass Estimation From GEDI Data and the US Forest Inventory JM Bruening, PB May, JD Armston, RO Dubayah Frontiers in Forests and Global Change 6, 1149153, 2023 | 4 | 2023 |
| GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1. ORNL DAAC, Oak Ridge, Tennessee, USA RO Dubayah, J Armston, JR Kellner, L Duncanson, SP Healey, ... | 4 | 2022 |
| GEDI L4B Gridded Aboveground Biomass Density, Version 2. ORNL DAAC, Oak Ridge, Tennessee, USA RO Dubayah, J Armston, SP Healey, Z Yang, PL Patterson, S Saarela, ... | 3 | 2017 |
| The GEDI gridded biomass product: patterns of coverage and precision after two years of operation S Healey, J Armston, Z Yang, R Dubayah, J Bruening, P Patterson, ... AGU Fall Meeting Abstracts 2021, B44D-05, 2021 | 1 | 2021 |
| Connecting spaceborne lidar with NFI networks: A method for improved estimation of forest structure and biomass PB May, RO Dubayah, JM Bruening, GC Gaines III International Journal of Applied Earth Observation and Geoinformation 129 …, 2024 | | 2024 |
| Definition criteria determine the success of old-growth mapping JM Bruening, RO Dubayah, N Pederson, B Poulter, L Calle Ecological Indicators 159, 111709, 2024 | | 2024 |
| Quality assessment of the GEDI waveform structural complexity index T de Conto, A Pascual, E Powell, J Bruening, JD Armston, R Dubayah AGU23, 2023 | | 2023 |
| GEDI-FIA Fusion Enables Precise and Unbiased Biomass Estimation JM Bruening, P May, JD Armston, R Dubayah AGU23, 2023 | | 2023 |
| On-orbit performance of GEDI aboveground biomass density algorithms. JR Kellner, JD Armston, L Duncanson, JB Blair, J Bruening, T de Conto, ... AGU23, 2023 | | 2023 |
| GEDI L4B Country-level Summaries of Aboveground Biomass J ARMSTON, RO DUBAYAH, SP HEALEY, Z YANG, PL PATTERSON, ... ORNL DAAC, 2023 | | 2023 |
Ralph DubayahUniversity of Maryland, Geographical SciencesVerified email at umd.edu
