フォロー
Laura Duncanson
Laura Duncanson
確認したメール アドレス: umd.edu
タイトル
引用先
引用先
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
8312020
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
2342022
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
2292019
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
2272020
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
2242014
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
2032010
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
1682020
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
1682019
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
1632021
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
1532019
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
1462019
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
1352017
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
1252022
Small sample sizes yield biased allometric equations in temperate forests
L Duncanson, O Rourke, R Dubayah
Scientific reports 5 (1), 17153, 2015
1172015
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
1112020
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
1012010
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
852015
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
832019
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
822015
Estimating forest above‐ground biomass with terrestrial laser scanning: Current status and future directions
M Demol, H Verbeeck, B Gielen, J Armston, A Burt, M Disney, ...
Methods in Ecology and Evolution 13 (8), 1628-1639, 2022
702022
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