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

/ X. Chi [et al.] // Atmospheric Chemistry and Physics. - 2013. - Vol. 13, Is. 24. - P12271-12298, DOI 10.5194/acp-13-12271-2013 . - ISSN 1680-7316
Аннотация: Siberia is one of few continental regions in the Northern Hemisphere where the atmosphere may sometimes approach pristine background conditions. We present the time series of aerosol and carbon monoxide (CO) measurements between September 2006 and December 2011 at the Zotino Tall Tower Observatory (ZOTTO) in Central Siberia (61° N; 89° E). We investigate the seasonal, weekly and diurnal variations of aerosol properties (including absorption and scattering coefficients and derived parameters, such as equivalent black carbon (BC e), Angstrom exponent, single scattering albedo, and backscattering ratio) and the CO mixing ratios. Criteria were established to distinguish polluted from near-pristine air masses, providing quantitative characteristics for each type. Depending on the season, 23-36% of the sampling time at ZOTTO was found to be representative of a clean atmosphere. The summer pristine data indicate that primary biogenic and secondary organic aerosol formation are quite strong particle sources in the Siberian taiga. The summer seasons 2007-2008 were dominated by an Aitken mode around 80 nm size, whereas the summer 2009 with prevailing easterly winds produced particles in the accumulation mode around 200 nm size. We found these differences to be mainly related to air temperature, through its effect on the production rates of biogenic volatile organic compounds (VOC) precursor gases. In winter, the particle size distribution peaked at 160 nm, and the footprint of clean background air was characteristic for aged particles from anthropogenic sources at great distances from ZOTTO and diluted biofuel burning emissions from domestic heating. The wintertime polluted air originates mainly from large cities south and southwest of the site; these particles have a dominant mode around 100 nm, and the ?BCe/?CO ratio of 7-11 ng m -3 ppb-1 suggests dominant contributions from coal and biofuel burning for heating. During summer, anthropogenic emissions are the dominant contributor to the pollution particles at ZOTTO, while only 12% of the polluted events are classified as biomass-burning-dominated, but then often associated with extremely high CO concentrations and aerosol absorption coefficients. Two biomass-burning case studies revealed different ΔBCe/?CO ratios from different fire types, with the agricultural fires in April?2008 yielding a very high ratio of 21 ng m -3 ppb-1. Overall, we find that anthropogenic sources dominate the aerosol population at ZOTTO most of the time, even during nominally clean episodes in winter, and that near-pristine conditions are encountered only in the growing season and then only episodically. © Author(s) 2013.

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Держатели документа:
Biogeochemistry Department, Max Planck Institute for Chemistry, 55020 Mainz, Germany
V. N. Sukachev Institute of Forest, Krasnoyarsk, 660036, Russian Federation
Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
Leibniz Institute for Tropospheric Research, 04318 Leipzig, Germany

Доп.точки доступа:
Chi, X.; Winderlich, J.; Mayer, J.-C.; Panov, A.V.; Heimann, M.; Birmili, W.; Heintzenberg, J.; Cheng, Y.; Andreae, M.O.

/ K. J. Ranson [et al.] // International Geoscience and Remote Sensing Symposium (IGARSS). - 2003. - Vol. 2: 2003 IGARSS: Learning From Earth's Shapes and Colours (21 July 2003 through 25 July 2003, Toulouse) Conference code: 61846. - P969-971 . -
Аннотация: Monitoring the dynamics of the tundra-taiga boundary is critical for our understanding of the causes and consequences of the changes in this area. Because of its inaccessibility, remote sensing data will play an important role. In this study we examined the use of several remote sensing techniques for identifying the existing tundra- taiga ecotone. These include Landsat, MISR and RADARSAT data. High-resolution IKONOS images were used for local ground truth. It was found that on Landsat ETM+ summer images, reflectance from tundra and taiga at band 4 (NIR) is similar, but different at other bands such as red, and MIR bands. When the incidence angle is small, C-band HH-pol backscattering coefficients from both tundra and taiga are relatively high. The backscattering from tundra targets decreases faster than taiga targets when the incidence angle increases, because the tundra targets look smoother than taiga. Because of the shading effect of the vegetation, the MISR data, both multi-spectral data at nadir looking and multi-angle data at red and NIR bands, clearly show the transition zone.

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Держатели документа:
NASA's Goddard Space Flight Center, Code 923, Greenbelt, MD, United States
Department of Geography, University of Maryland, College Park, MD, United States
V.N. Sukachev Institute of Forest, Academgorodok, Krasnoyarsk, Russian Federation
Sci. Systems and Applications, Inc., Lanham, MD, United States

Доп.точки доступа:
Ranson, K.J.; Sun, G.; Kharuk, V.I.; Kovacs, K.

/ G. Sun, K. J. Ranson, V. I. Kharuk // Remote Sensing of Environment. - 2002. - Vol. 79, Is. 2-3. - P279-287, DOI 10.1016/S0034-4257(01)00279-6 . - ISSN 0034-4257
Аннотация: We investigated the possibility of using multiple polarization (SIR-C) L-band data to map forest biomass in a mountainous area in Siberia. The use of a digital elevation model (DEM) and a model-based method for reducing terrain effects was evaluated. We found that the available DEM data were not suitable to correct the topographic effects on the SIR-C radar images. A model-based slope correction was applied to an L-band cross-polarized (hv) backscattering image and found to reduce the topographic effect. A map of aboveground biomass was produced from the corrected image. The results indicated that multipolarization L-band synthetic aperture radar (SAR) data can be useful for estimation of total aboveground biomass of forest stands in mountainous areas. В© 2002 Elsevier Science Inc. All rights reserved.

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Держатели документа:
Department of Geography, University of Maryland, College Park, MD 20742, United States
NASA's Goddard Space Flight Center, Code 923, Greenbelt, MD 20771, United States
Sukachev Institute of Forest, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Sun, G.; Ranson, K.J.; Kharuk, V.I.

/ W. J. Ni, G. Q. Sun, K. J. Ranson [et al.] // 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS : IEEE, 2019. - IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (JUL 28-AUG 02, 2019, Yokohama, JAPAN). - P4892-4895. - (IEEE International Symposium on Geoscience and Remote Sensing IGARSS). - Cited References:15. - This study is sponsored by National Key R&D Program of China (2017YFA0603002), National Natural Science Foundation of China (Grant No. 41471311), National Basic Research Program of China (Grant No. 2013CB733401, 2013CB733404). . - РУБ Geosciences, Multidisciplinary + Remote Sensing

Аннотация: The accurate mapping of forest AGB using remote sensing dataset is hindered by the saturation problem and the terrain effects. Direct measurement of forest spatial structures and terrains should be the solutions of these problems. However, the information of forest vertical structure and ground surface terrain are always mixed together in remote sensing datasets which can directly measure the elevations of ground objects. One potential way is to separate them is to synthesize InSAR, stereo imagery and lidar waveform. Theoretical model is needed for this effort. In this study, a unified model was presented, which can be used to simulate InSAR, stereo imagery and lidar waveforms over mountainous forest landscapes.

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Держатели документа:
Chinese Acad Sci, Inst Remote Sensing Applicat, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.
Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA.
NASA, Biospher Sci Lab, Goddard Space Flight Ctr, Code 618, Greenbelt, MD 20771 USA.
Sci Syst & Applicat Inc, 10210 Greenbelt Rd, Lanham, MD 20706 USA.
Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China.
Siberian Fed Univ, VN Sukachev Inst Forest, Krasnoyarsk 660036, Russia.

Доп.точки доступа:
Ni, Wenjian; Sun, Guoqing; Ranson, Kenneth Jon; Montesano, Paul; Liu, Qinhuo; Li, Zengyuan; Kharuk, Vyacheslav I.; Zhang, Zhiyu; National Key R&D Program of China [2017YFA0603002]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [41471311]; National Basic Research Program of ChinaNational Basic Research Program of China [2013CB733401, 2013CB733404]