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

[Text] / G. . Sun [et al.] // Remote Sens. Environ. - 2003. - Vol. 88, Is. 4. - P401-411, DOI 10.1016/j.rse.2003.09.001. - Cited References: 28 . - 11. - ISSN 0034-4257РУБ Environmental Sciences + Remote Sensing + Imaging Science & Photographic Technology

Аннотация: Spaceborne Interferometric SAR (InSAR) technology used in the Shuttle Radar Topography Mission (SRTM) and spaceborne lidar such as Shuttle Laser Altimeter-02 (SLA-02) are two promising technologies for providing global scale digital elevation models (DEMs). Each type of these systems has limitations that affect the accuracy or extent of coverage. These systems are complementary in developing DEM data. In this study, surface height measured independently by SRTM and SLA-02 was cross-validated. SLA data was first verified by field observations, and examinations of individual lidar waveforms. The geolocation accuracy of the SLA height data sets was examined by checking the correlation between the SLA surface height with SRTM height at 90 in resolution, while shifting the SLA ground track within its specified horizontal errors. It was found that the heights from the two instruments were highly correlated along the SLA ground track, and shifting the positions did not improve the correlation significantly. Absolute surface heights from SRTM and SLA referenced to the same horizontal and vertical datum (World Geodetic System (WGS) 84 Ellipsoid) were compared. The effects of forest cover and surface slope on the height difference were also examined. After removing the forest effect on SRTM height, the mean height difference with SLA-02 was near zero. It can be further inferred from the standard deviation of the height differences that the absolute accuracy of SRTM height at low vegetation area is better than the SRTM mission specifications (16 in). The SRTM height bias caused by forest cover needs to be further examined using future spaceborne lidar (e.g. GLAS) data. (C) 2003 Elsevier Inc. All rights reserved.

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Держатели документа:
Univ Maryland, Dept Geog, College Pk, MD 20742 USA
NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA
VN Sukachev Inst Forest, Krasnoyarsk, Russia
Sci Syst & Applicat Inc, Lanham, MD 20706 USA

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Sun, G...; Ranson, K.J.; Khairuk, V.I.; Kovacs, K...

[Text] / CSR Neigh [et al.] // Remote Sens. Environ. - 2013. - Vol. 137. - P274-287, DOI 10.1016/j.rse.2013.06.019. - Cited References: 75. - This study was made possible by NASA's Terrestrial Ecology program under grants NNH08ZDA001N-TE and NNH06ZDA001N-CARBON. We also acknowledge the NSERC Discovery Grant to Hank Margolis for contributing partial support for the airborne data collection in Canada. We would like to thank three anonymous reviewers who improved the quality and content of this manuscript. We would also like to thank Sergi Im, Mukhtar Naurzbaev, Pasha Oskorbin, and Marsha Dvinskaya of the Sukachev Institute of Forest and Bruce Cook from the NASA Goddard Space Flight Center for help in collecting field measurements in Siberia. . - 14. - ISSN 0034-4257РУБ Environmental Sciences + Remote Sensing + Imaging Science & Photographic Technology

Аннотация: The boreal forest accounts for one-third of global forests, but remains largely inaccessible to ground-based measurements and monitoring. It contains large quantities of carbon in its vegetation and soils, and research suggests that it will be subject to increasingly severe climate-driven disturbance. We employ a suite of ground-, airborne- and space-based measurement techniques to derive the first satellite LiDAR-based estimates of aboveground carbon for the entire circumboreal forest biome. Incorporating these inventory techniques with uncertainty analysis, we estimate total aboveground carbon of 38 +/- 3.1 Pg. This boreal forest carbon is mostly concentrated from 50 to 55 degrees N in eastern Canada and from 55 to 60 degrees N in eastern Eurasia. Both of these regions are expected to warm >3 degrees C by 2100, and monitoring the effects of warming on these stocks is important to understanding its future carbon balance. Our maps establish a baseline for future quantification of circumboreal carbon and the described technique should provide a robust method for future monitoring of the spatial and temporal changes of the aboveground carbon content. Published by Elsevier Inc.

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Держатели документа:
[Neigh, Christopher S. R.
Nelson, Ross F.
Ranson, K. Jon
Montesano, Paul M.
Sun, Guoqing] NASA, Biospher Sci Lab, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA
[Margolis, Hank A.] Univ Laval, Ctr Etud Foret, Quebec City, PQ G1V 0A6, Canada
[Montesano, Paul M.] Sigma Space Corp, Lanham, MD 20705 USA
[Montesano, Paul M.
Sun, Guoqing] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
[Kharuk, Viacheslav] Russian Acad Sci, Sukachev Inst Forest, Krasnoyarsk 660036, Russia
[Naesset, Erik] Norwegian Univ Life Sci, Dept Ecol & Nat Resource Management, NO-1432 As, Norway
[Wulder, Michael A.] Nat Resources Canada, Pacific Forestry Ctr, Canadian Forest Serv, Victoria, BC V82Z 1M5, Canada
[Andersen, Hans-Erik] Univ Washington, US Forest Serv, Pacific NW Res Stn, Seattle, WA 98195 USA

Доп.точки доступа:
Neigh, CSR; Nelson, R.F.; Ranson, K.J.; Margolis, H.A.; Montesano, P.M.; Sun, G.Q.; Kharuk, V...; Naesset, E...; Wulder, M.A.; Andersen, H.E.; NASA [NNH08ZDA001N-TE, NNH06ZDA001N-CARBON]; NSERC Discovery Grant

/ K. J. Ranson [et al.] // International Geoscience and Remote Sensing Symposium (IGARSS). - 2007. - 2007 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2007 (23 June 2007 through 28 June 2007, Barcelona) Conference code: 71398. - Ст. 4423302. - P2306-2309, DOI 10.1109/IGARSS.2007.4423302 . -
Аннотация: Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. The biggest deficiency of the existing ground based forest inventories is the uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse, lacking, and often decades old. Remote sensing methods can overcome these problems. In this study, we used the moderate resolution imaging spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) and produced a map of timber volume for a 10В°?12В° area in Central Siberia. Using these methods, the mean timber volume for the forested area in the total study area was 203 m3/ ha. The new remote sensing methods used in this study provide a truly independent estimate of forest structure, which is not dependent on traditional ground forest inventory methods. В© 2007 IEEE.

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Держатели документа:
NASA GSFC, Code 614.4, Greenbelt, MD 20771, United States
Department of Geography, University of Maryland, College Park, MD 20742, United States
Sukachev Institute of Forest, Krasnoyarsk, Russian Federation
Science Systems and Applications Inc., Lanham, MD 20706, United States

Доп.точки доступа:
Ranson, K.J.; Nelson, R.; Kimes, D.; Sun, G.; Kharuk, V.; Montesano, P.

/ K. J. Ranson [et al.] // International Geoscience and Remote Sensing Symposium (IGARSS). - 2004. - Vol. 2: 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004 (20 September 2004 through 24 September 2004, Anchorage, AK) Conference code: 64488. - P753-756 . -
Аннотация: NASA's ICESat Geoscience Laser Altimeter System (GLAS) was launched in January 2003 and collected lidar data during February and September of that year. Lidar is a laser altimeter that measures the distance from the instrument to the surface by measuring the time elapsed between the pulse emission and the reflected return. The returned signal may identify multiple returns originating from trees, buildings and other objects and permits the calculation of their height. Sampling the returns at discrete time intervals enables backscatter profiles to be constructed. Lidar data can provide estimates of other structural parameters such as biomass, stand volume and leaf area. This study used GLAS data acquired over our study sites in central Siberia to examine the signal as a source of information of forest stand characteristics. Example lidar profiles are presented and preliminary analysis is described. The results indicate that GLAS profile information may be useful for understanding MODIS landcover classes.

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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, United States
Sci. Systems and Applications, Inc., Seabrook, MD, United States
V.N. Sukachev Institute of Forest, Academgorodok, Krasnoyarsk, Russian Federation

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

/ K. J. Ranson [et al.] // International Geoscience and Remote Sensing Symposium (IGARSS). - 2004. - Vol. 3: 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004 (20 September 2004 through 24 September 2004, Anchorage, AK) Conference code: 64488. - P1936-1939 . -
Аннотация: Lidar is a laser altimeter that determines the distance from the instrument to the physical surface by measuring the time elapsed between the pulse emission and the reflected return. The returned signal may identify multiple returns originating from trees, building and other objects and permits the calculation of their height. Studies using field data have shown that lidar data can provide estimates of structural parameters such as biomass, stand volume and leaf area index. NASA's ICESat Geoscience Laser Altimeter System (GLAS) was launched in January 2003 and collected data during February and September of that year. This study used GLAS data acquired over our study sites in central Siberia to examine the returned signal as a source of information about fire and insect damaged forest stands.

Scopus

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

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

/ R. Nelson [et al.] // Remote Sens. Environ. - 2009. - Vol. 113, Is. 3. - P691-701, DOI 10.1016/j.rse.2008.11.010 . - ISSN 0034-4257
Аннотация: Geosciences Laser Altimeter System (GLAS) space LiDAR data are used to attribute a MODerate resolution Imaging Spectrometer (MODIS) 500В m land cover classification of a 10В° latitude by 12В° longitude study area in south-central Siberia. Timber volume estimates are generated for 16 forest classes, i.e., four forest cover types ? four canopy density classes, across this 811,414В km 2 area and compared with a ground-based regional volume estimate. Two regional GLAS/MODIS timber volume products, one considering only those pulses falling on slopes ? 10В° and one utilizing all GLAS pulses regardless of slope, are generated. Using a two-phase(GLAS-ground plot) sampling design, GLAS/MODIS volumes average 163.4 В± 11.8В m 3/ha across all 16 forest classes based on GLAS pulses on slopes ? 10В° and 171.9 В± 12.4В m 3/ha considering GLAS shots on all slopes. The increase in regional GLAS volume per-hectare estimates as a function of increasing slope most likely illustrate the effects of vertical waveform expansion due to the convolution of topography with the forest canopy response. A comparable, independent, ground-based estimate is 146В m 3/ha [Shepashenko, D., Shvidenko, A., and Nilsson, S. (1998). Phytomass (live biomass) and carbon of Siberian forests. Biomass and Bioenergy, 14, 21-31], a difference of 11.9% and 17.7% for GLAS shots on slopes ? 10В° and all GLAS shots regardless of slope, respectively. A ground-based estimate of total volume for the entire study area, 7.46 ? 10 9В m 3, is derived using Shepashenko et al.'s per-hectare volume estimate in conjunction with forest area derived from a 1990 forest map [Grasia, M.G. (ed.). (1990). Forest Map of USSR. Soyuzgiproleskhoz, Moscow, RU. Scale: 1:2,500,000]. The comparable GLAS/MODIS estimate is 7.38 ? 10 9В m 3, a difference of less than 1.1%. Results indicate that GLAS data can be used to attribute digital land cover maps to estimate forest resources over subcontinental areas encompassing hundreds of thousands of square kilometers.

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Держатели документа:
Biospheric Sciences Branch, NASA/Goddard Space Flight Center, Code 614.4, Greenbelt, MD 20771, United States
Department of Geography, University of Maryland, College Park, MD 20742, United States
Sukachev Forest Institute, Krasnoyarsk-36, Academgorodok, Russian Federation
Science Systems and Applications, Inc., Lanham, MD 20706, United States

Доп.точки доступа:
Nelson, R.; Ranson, K.J.; Sun, G.; Kimes, D.S.; Kharuk, V.; Montesano, P.

/ P. M. Montesano [et al.] // Remote Sens. Environ. - 2014. - Vol. 154. - P398-407, DOI 10.1016/j.rse.2014.01.027 . - ISSN 0034-4257
Аннотация: In this study, we examined the uncertainty of aboveground live biomass (AGB) estimates based on light detection and ranging (LiDAR) and synthetic aperture radar (SAR) measurements distributed across a low-biomass vegetation structure gradient from forest to non-forest in boreal-like ecosystems. The conifer-dominant structure gradient was compiled from ground data amassed from multiple field expeditions in central Maine (USA), Aurskog (Norway), and across central Siberia (Russia). Single variable empirical models were built to model AGB from remote sensing metrics. Using these models, we calculated a root mean square error (RMSE) and a 95% confidence interval (CI) of the RMSE from the difference between the remote sensing AGB predictions and the ground reference AGB estimates within AGB intervals across a 0-100Mgha-1 boreal forest structure gradient. The results show that the error in AGB predictions (RMSE) and the error uncertainty (the CI) from LiDAR and SAR change across a forest gradient. The errors of airborne LiDAR and SAR metrics and spaceborne LiDAR platforms show a general trend of reduced relative errors as AGB magnitudes increase, particularly from 0 to 60Mgha-1. Empirical models relating spaceborne metrics to AGB and estimates of spaceborne LiDAR error uncertainty demonstrate the difficulty of characterizing differences in AGB at the site-level with current spaceborne sensors, particularly below 80Mgha-1 with less than 50-100% error.

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Держатели документа:
University of Maryland, Department of Geographical SciencesCollege Park, MD, United States
Sigma Space Corp.Lanham, MD, United States
Code 618,Biospheric Sciences Branch, NASA/Goddard Space Flight CenterGreenbelt, MD, United States
Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003As, Norway
Sukachev Institute of Forest, Siberian Branch, Russian Academy of SciencesAkademgorodok, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Montesano, P.M.; Nelson, R.F.; Dubayah, R.O.; Sun, G.; Cook, B.D.; Ranson, K.J.R.; N?sset, E.; Kharuk, V.

[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.
ИЛ СО РАН

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

/ M. Favorskaya [et al.] // Smart Innovation, Systems and Technologies. - 2015. - Vol. 40: 8th KES International Conference on Intelligent Interactive Multimedia Systems and Services, IIMSS-2015; Sorrento; Italy; 17 June 2015 through 19 June 2015; Code 157679. - P191-201, DOI 10.1007/978-3-319-19830-9_18 . -
Аннотация: During airborne laser scanning, different types of information are available including Light Detection And Ranging (LiDAR) data as a cloud of 3D points, aerial digital photography data (hyperspectral or color visual images), and additional information about parameters of shooting. Difficulties of large image stitching due to parallax effects lead to distortions between ground truth 3D LiDAR coordinates and 2D visual coordinates of the same point. Our contribution is to develop a method for fusion of LiDAR and visual information for accurate segmentation of individual tree crowns in order to receive biomass measurements. The shearlet theory was used to improve boundaries and texture of airborne images. Also in this paper, a higher-order active contour model is applied for area evaluation of tree crowns in a plane. The received area measurements are promising and coincide with expert estimations providing accuracy 92–96%. The modeling results are good for non-Lambert space of forest. © Springer International Publishing Switzerland 2015.

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Держатели документа:
Siberian State Aerospace University, Institute of Informatics and Telecommunications, 31 Krasnoyarsky Rabochy, Krasnoyarsk, Russian Federation
Institute of Forest Russian Academy of Sciences, Siberian Branch, Akademgorodok, 50/28, Krasnoyarsk, Krasnoyarsk, Russian Federation
Department of Geography and Human Environment, Tel Aviv University, Ramat Aviv, Tel Aviv, Israel

Доп.точки доступа:
Favorskaya, M.; Tkacheva, A.; Danilin, I. M.; Medvedev, E. M.

[Текст] : статья / Дмитрий Геннадьевич Щепащенко [и др.] // Сибирский лесной журнал. - 2017. - № : 4. - С. 3-11, DOI 10.15372/SJFS20170401 . - ISSN 2311-1410
   Перевод заглавия: Forest biomass observation: current state and prospective

УДК

528.8

581.5

Аннотация: Дан обзор современных методов, инструментов и перспектив мониторинга лесной фитомассы в глобальном масштабе. Рассмотрены преимущества и недостатки различных дистанционных методов космического базирования, включая оптические, радарные (C-, L-, P-диапазонов) и лазерные, а также соответствующие им инструменты, находящиеся на орбите (MODIS, Proba-V, Landsat, Sentinel-1, Sentinel-2, ALOS PALSAR, Envisat ASAR) или готовящиеся к запуску (BIOMASS, GEDI, NISAR, SAOCOM-CS). Подчеркнута роль наземных методов в разработке моделей фитомассы, обеспечении калибровки и проверки дистанционных данных. Описаны имеющиеся в свободном доступе карты, базы данных и эмпирические модели (как подеревные - аллометрические, так и на уровне насаждений) лесной фитомассы. Описаны функциональные возможности интернет-портала Biomass.Geo-Wiki.org, который предоставляет доступ к коллекции глобальных и региональных карт фитомассы в полном разрешении с унифицированной легендой, наложенных на снимки высокого разрешения. Анонсирована международная кооперация ученых, проводящих измерения на постоянных пробных площадях (Forest Observation System), и рассмотрены ее перспективы в развитии сети наземных наблюдений во взаимодействии с дистанционным сообществом. Кратко рассмотрены перспективы беспилотных летательных аппаратов в инвентаризации лесов. Авторы адресуют данный обзор специалистам лесного хозяйства и научным работникам в области лесоведения и экологии, которые не являются экспертами в дистанционном зондировании, но хотят получить представление о современных тенденциях в этой области знания. Также статья нацелена на уменьшение разобщенности научных коллективов и более широкий обмен данными и знаниями между дистанционным и экологическим сообществами.
With this article, we provide an overview of the methods, instruments and initiatives for forest biomass observation at global scale. We focus on the freely available information, provided by both remote and in-situ observations. The advantages and limitation of various space borne methods, including optical, radar (C, L and P band) and LiDAR, as well as respective instruments available on the orbit (MODIS, Proba-V, Landsat, Sentinel-1, Sentinel-2, ALOS PALSAR, Envisat ASAR) or expecting (BIOMASS, GEDI, NISAR, SAOCOM-CS) are discussed. We emphasize the role of in-situ methods in the development of a biomass models, providing calibration and validation of remote sensing data. We focus on freely available forest biomass maps, databases and empirical models. We describe the functionality of Biomass.Geo-Wiki.org portal, which provides access to a collection of global and regional biomass maps in full resolution with unified legend and units overplayed with high-resolution imagery. The Forest-Observation-System.net is announced as an international cooperation to establish a global in-situ forest biomass database to support earth observation and to encourage investment in relevant field-based observations and science. Prospects of unmanned aerial vehicles in the forest inventory are briefly discussed.

РИНЦ

Держатели документа:
Ботанический сад УрО РАН
Всероссийский институт повышения квалификации руководящих работников и специалистов лесного хозяйства
Институт биологии Коми научного центра УрО РАН
Институт леса им. В. Н. Сукачева СО РАН
Международный институт прикладного системного анализа
Московский государственный технический университет им. Н. Э. Баумана
Национальный университет биоресурсов и природопользования Украины

Доп.точки доступа:
Щепащенко, Дмитрий Геннадьевич; Schepaschenko D.G.; Осипов, Андрей Федорович; Osipov A.F.; Мартыненко, Ольга Вениаминовна; Martynenko O.V.; Карминов, Виктор Николаевич; Karminov V.N.; Онтиков, Пётр Вячеславович; Ontikov P.V.; Щепащенко, Мария Владимировна; Shchepashchenko M.V.; Кракснер, Флориан; Kraxner F.; Швиденко, Анатолий Зиновьевич; Shvidenko A.Z.; Пергер, Кристоф; Perger C.; Дресел, Кристофер; Dresel C.; Фриц, Штефен; Fritz S.; Лакида, Петр Иванович; Lakyda P.I.; Мухортова, Людмила Владимировна; Mukhortova L.V.; Усольцев, Владимир Андреевич; Usoltsev V.A.; Бобкова, Капитолина Степановна; Bobkova K.S.

/ W. Ni, G. Sun, K. J. Ranson [et al.] // International Geoscience and Remote Sensing Symposium (IGARSS) : Institute of Electrical and Electronics Engineers Inc., 2019. - 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 (28 July 2019 through 2 August 2019, ) Conference code: 154792. - P4892-4895, DOI 10.1109/IGARSS.2019.8898106 . -
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. © 2019 IEEE.

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Держатели документа:
Institute of Remote Sensing Applications of Chinese Academy of Sciences, State Key Laboratory of Remote Sensing Science, Beijing, 100101, China
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, United States
Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, United States
Science Systems and Applications, Inc., 10210 Greenbelt Road, Lanham, MD 20706, United States
Institute of Forest Resource Information Technique, Chinese Academy of Forestry, Beijing, 100091, China
VN Sukachev Institute of Forest, Siberian Federal University, Krasnoyarsk, 660036, Russian Federation

Доп.точки доступа:
Ni, W.; Sun, G.; Ranson, K. J.; Montesano, P.; Liu, Q.; Li, Z.; Kharuk, V. I.; Zhang, Z.

/ 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.

WOS

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]