| The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography R Dubayah, JB Blair, S Goetz, L Fatoyinbo, M Hansen, S Healey, ... Science of remote sensing 1, 100002, 2020 | 584 | 2020 |
| An efficient, multi-layered crown delineation algorithm for mapping individual tree structure across multiple ecosystems LI Duncanson, BD Cook, GC Hurtt, RO Dubayah Remote Sensing of Environment 154, 378-386, 2014 | 210 | 2014 |
| Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California L Duncanson, A Neuenschwander, S Hancock, N Thomas, T Fatoyinbo, ... Remote Sensing of Environment 242, 111779, 2020 | 185 | 2020 |
| Estimating forest canopy height and terrain relief from GLAS waveform metrics LI Duncanson, KO Niemann, MA Wulder Remote Sensing of Environment 114 (1), 138-154, 2010 | 185 | 2010 |
| The GEDI simulator: A large‐footprint waveform lidar simulator for calibration and validation of spaceborne missions S Hancock, J Armston, M Hofton, X Sun, H Tang, LI Duncanson, ... Earth and Space Science 6 (2), 294-310, 2019 | 162 | 2019 |
| The importance of consistent global forest aboveground biomass product validation L Duncanson, J Armston, M Disney, V Avitabile, N Barbier, K Calders, ... Surveys in geophysics 40, 979-999, 2019 | 128 | 2019 |
| ISS observations offer insights into plant function EN Stavros, D Schimel, R Pavlick, S Serbin, A Swann, L Duncanson, ... Nature Ecology & Evolution 1 (7), 0194, 2017 | 124 | 2017 |
| Ground data are essential for biomass remote sensing missions J Chave, SJ Davies, OL Phillips, SL Lewis, P Sist, D Schepaschenko, ... Surveys in Geophysics 40, 863-880, 2019 | 123 | 2019 |
| 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 | 119 | 2022 |
| New opportunities for forest remote sensing through ultra-high-density drone lidar JR Kellner, J Armston, M Birrer, KC Cushman, L Duncanson, C Eck, ... Surveys in Geophysics 40, 959-977, 2019 | 114 | 2019 |
| Validation of ICESat-2 terrain and canopy heights in boreal forests A Neuenschwander, E Guenther, JC White, L Duncanson, P Montesano Remote Sensing of Environment 251, 112110, 2020 | 112 | 2020 |
| Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping CA Silva, L Duncanson, S Hancock, A Neuenschwander, N Thomas, ... Remote Sensing of Environment 253, 112234, 2021 | 104 | 2021 |
| Small sample sizes yield biased allometric equations in temperate forests L Duncanson, O Rourke, R Dubayah Scientific reports 5 (1), 17153, 2015 | 103 | 2015 |
| Integration of GLAS and Landsat TM data for aboveground biomass estimation LI Duncanson, KO Niemann, MA Wulder Canadian Journal of Remote Sensing 36 (2), 129-141, 2010 | 96 | 2010 |
| Towards mapping the diversity of canopy structure from space with GEDI FD Schneider, A Ferraz, S Hancock, LI Duncanson, RO Dubayah, ... Environmental Research Letters 15 (11), 115006, 2020 | 81 | 2020 |
| Assessing the general patterns of forest structure: Quantifying tree and forest allometric scaling relationships in the U nited S tates LI Duncanson, RO Dubayah, BJ Enquist Global Ecology and Biogeography 24 (12), 1465-1475, 2015 | 75 | 2015 |
| The importance of spatial detail: Assessing the utility of individual crown information and scaling approaches for lidar-based biomass density estimation LI Duncanson, RO Dubayah, BD Cook, J Rosette, G Parker Remote Sensing of Environment 168, 102-112, 2015 | 75 | 2015 |
| 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 | 61 | 2022 |
| Statistical properties of hybrid estimators proposed for GEDI—NASA’s global ecosystem dynamics investigation PL Patterson, SP Healey, G Ståhl, S Saarela, S Holm, HE Andersen, ... Environmental Research Letters 14 (6), 065007, 2019 | 58 | 2019 |
| A semiautomated probabilistic framework for tree-cover delineation from 1-m NAIP imagery using a high-performance computing architecture S Basu, S Ganguly, RR Nemani, S Mukhopadhyay, G Zhang, C Milesi, ... IEEE Transactions on Geoscience and Remote Sensing 53 (10), 5690-5708, 2015 | 52 | 2015 |
