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The Uncertainty of Biomass Estimates from Modeled ICESat-2 Returns Across a Boreal Forest GradientThe Forest Light (FLIGHT) radiative transfer model was used to examine the uncertainty of vegetation structure measurements from NASA's planned ICESat-2 photon counting light detection and ranging (LiDAR) instrument across a synthetic Larix forest gradient in the taiga-tundra ecotone. The simulations demonstrate how measurements from the planned spaceborne mission, which differ from those of previous LiDAR systems, may perform across a boreal forest to non-forest structure gradient in globally important ecological region of northern Siberia. We used a modified version of FLIGHT to simulate the acquisition parameters of ICESat-2. Modeled returns were analyzed from collections of sequential footprints along LiDAR tracks (link-scales) of lengths ranging from 20 m-90 m. These link-scales traversed synthetic forest stands that were initialized with parameters drawn from field surveys in Siberian Larix forests. LiDAR returns from vegetation were compiled for 100 simulated LiDAR collections for each 10 Mg · ha(exp -1) interval in the 0-100 Mg · ha(exp -1) above-ground biomass density (AGB) forest gradient. Canopy height metrics were computed and AGB was inferred from empirical models. The root mean square error (RMSE) and RMSE uncertainty associated with the distribution of inferred AGB within each AGB interval across the gradient was examined. Simulation results of the bright daylight and low vegetation reflectivity conditions for collecting photon counting LiDAR with no topographic relief show that 1-2 photons are returned for 79%-88% of LiDAR shots. Signal photons account for approximately 67% of all LiDAR returns, while approximately 50% of shots result in 1 signal photon returned. The proportion of these signal photon returns do not differ significantly (p greater than 0.05) for AGB intervals greater than 20 Mg · ha(exp -1). The 50m link-scale approximates the finest horizontal resolution (length) at which photon counting LiDAR collection provides strong model fits and minimizes forest structure uncertainty in the synthetic Larix stands. At this link-scale AGB greater than 20 Mg · ha(exp -1) has AGB error from 20-50% at the 95% confidence level. These results suggest that the theoretical sensitivity of ICESat-2 photon counting LiDAR measurements alone lack the ability to consistently discern differences in inferred AGB at 10 Mg · ha(exp -1) intervals in sparse forests characteristic of the taiga-tundra ecotone.
Document ID
20160005010
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Montesano, P. M.
(Maryland Univ. College Park, MD, United States)
Rosette, J.
(University Coll. Swansea, United Kingdom)
Sun, G.
(Maryland Univ. College Park, MD, United States)
North, P.
(University Coll. Swansea, United Kingdom)
Nelson, R. F.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Dubayah, R. O.
(Maryland Univ. College Park, MD, United States)
Ranson, K. J.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Kharuk, V.
(Academy of Sciences (Russia) Krasnoyarsk, Russian Federation)
Date Acquired
April 12, 2016
Publication Date
December 1, 2014
Publication Information
Publication: Remote Sensing of Environment
Publisher: Elsevier
Volume: 158
ISSN: 0034-4257
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN31162
Funding Number(s)
CONTRACT_GRANT: NNX12AD03A
Distribution Limits
Public
Copyright
Other
Keywords
LiDAR
Ecotone
Radiative transfer model

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