Труды сотрудников ИЛ им. В.Н. Сукачева СО РАН

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    The uncertainty of biomass estimates from modeled ICESat-2 returns across a boreal forest gradient
[Text] / P. M. Montesano [et al.] // Remote Sens. Environ. - 2015. - Vol. 158. - P95-109, DOI 10.1016/j.rse.2014.10.029. - Cited References:90. - This work was supported by the NASA Terrestrial Ecology Program. Weacknowledge the expertise of Sergey Im, Pasha Oskorbin and MukhtarNaurzbaev that was critical to the success of various field expeditionsin remote areas of northern Siberia. We also acknowledge the importanceof the constructive criticism provided by the anonymous reviewers whohelped improve this manuscript. . - ISSN 0034-4257. - ISSN 1879-0704
РУБ Environmental Sciences + Remote Sensing + Imaging Science & Photographic
Рубрики:
RADIATIVE-TRANSFER MODEL
   WAVE-FORM LIDAR

   SIBERIAN LARCH

Кл.слова (ненормированные):
Ecotone -- LiDAR -- Radiative transfer model -- Forest biomass -- Uncertainty -- Spaceboume

Аннотация: The 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(-1) interval in the 0-100 Mg . ha-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 similar to 67% of all LiDAR returns, while similar to 50% of shots result in 1 signal photon returned. The proportion of these signal photon returns do not differ significantly (p > 0.05) for AGB intervals >20 Mg . ha(-1). The 50 m 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 >20 Mg . ha(-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-1 intervals in sparse forests characteristic of the taiga-tundra ecotone. (C) 2014 Elsevier Inc. All rights reserved.

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Держатели документа:
Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA.
Sigma Space Corp, Lanham, MD 20706 USA.
NASA, Goddard Space Flight Ctr, Biospher Sci Branch, Greenbelt, MD 20771 USA.
Swansea Univ, Dept Geog, Swansea SA2 8PP, W Glam, Wales.
No Res Stn, Roslin EH26 9SY, Midlothian, Scotland.
Russian Acad Sci, Sukachev Inst Forest, Siberian Branch, Krasnoyarsk 660036, Russia.
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Доп.точки доступа:
Montesano, P. M.; Rosette, J.; Sun, G.; North, P.; Nelson, R.F.; Dubayah, R.O.; Ranson, K.J.; Kharuk, V.; NASA Terrestrial Ecology Program