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

[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 1879-0704РУБ Environmental Sciences + Remote Sensing + Imaging Science & Photographic

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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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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Montesano, P. M.; Rosette, J.; Sun, G.; North, P.; Nelson, R.F.; Dubayah, R.O.; Ranson, K.J.; Kharuk, V.; NASA Terrestrial Ecology Program

/ X. Huang [et al.] // Soil Biol. Biochem. - 2017. - Vol. 113. - P71-79, DOI 10.1016/j.soilbio.2017.05.021 . - ISSN 0038-0717
Аннотация: Many soil functions are modulated by processes at soil biogeochemical interfaces (BGIs). However, characterizing the elemental dynamics at BGIs is hampered by the heterogeneity of soil microenvironments. In order to investigate the processes of BGI formation in an upland soil (Mollisol) and a paddy soil (Oxisol), we developed a SoilChip method by assembling dispersed soil particles onto homogeneous 800-?m-diameter microarray chips and then submerging them in a solution that contained dissolved organic matter (OM) extracted from one of the two soils. The chips with Mollisol particles were incubated at 95–100% humidity, whereas the chips with Oxisol particles were incubated at 100% humidity. Dynamics of individual elements at the soils’ BGIs were quantitatively determined using X-ray photoelectron spectroscopy (XPS). Distinct differences in the soil-microbe complexes and elemental dynamics between the Mollisol and Oxisol BGIs suggested that the formation of specific BGIs resulted from the complex interaction of physical, chemical, and microbial processes. By integrating the SoilChip and XPS, it was possible to elucidate the dynamic formation of the two different soil BGIs under standardized conditions. Therefore, the SoilChip method is a promising tool for investigating micro-ecological processes in soil. © 2017

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Key Laboratory of Agro-ecological Processes in the Subtropical Region, Institute of Subtropical Agriculture, The Chinese Academy of Sciences, Changsha, China
University of Chinese Academy of Sciences, Beijing, China
Britton Chance Center for Biomedical Photonics at Wuhan National Laboratory for Optoelectronics – Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
Institute of Soil Science, Leibniz Universitat Hannover, Hannover, Germany
VN Sukachev Institute of Forest, Russian Academy of Sciences - Siberian Branch, Akademgorodok, Krasnoyarsk, Russian Federation
Key Laboratory of Arable Land Conservation (Middle and Lower Reaches of Yangtze River), Ministry of Agriculture, College of Resources and Environment, Huazhong Agricultural University, Wuhan, China

Доп.точки доступа:
Huang, X.; Li, Y.; Liu, B.; Guggenberger, G.; Shibistova, O.; Zhu, Z.; Ge, T.; Tan, W.; Wu, J.