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

/ С.Т. Им, С.М. Горожанкина, В.И. Харук, Дж.К. Рэнсон // Исследование земли из космоса. - 2004. - № 4. - С. 30-40. - Библиогр. в конце ст.
Аннотация: Анализируются вопросы применения данных с ИСЗ “Radarsat” для картирования растительности на восточной окраине Западной Сибири. Согласно зональному членению территории выбраны четыре тестовых участка, охватывающих тундру, лесотундру и таежную зону. Кроме яркостных свойств радиолокационной информации (РЛИ) в анализе применялись и текстурные характеристики изображения, а также данные о рельефе местности. По каждому тестовому участку созданы сигнатуры основных классов растительности. Выполнен сравнительный анализ сигнатур при использовании лишь яр-костной информации, пяти- и шестислойного композитов. Применение только яркостного микроволнового изображения в задачах классификации дает в целом неудовлетворительные результаты либо вообще не позволяет разделять леса по породному составу. Использование шестислойного композита существенно уменьшает ошибки классификации по сравнению с использованием только поля яркости. Анализ информативности показал следующую последовательность слоев в порядке уменьшения их значимости: рельеф, поле яркости, асимметрия, дисперсия, среднее Евклидово расстояние и эксцесс.

Информация о публикации

Держатели документа:
Институт леса им. В.Н. Сукачева Сибирского отделения Российской академии наук : 660036 Красноярск, Академгородок 50/28

Доп.точки доступа:
Им, Сергей Тхекдеевич; Im, Sergey Tkhekdyeyevich; Горожанкина, Светлана Михайловна; Gorozhankina Svetlana Mikhaylovna; Харук, Вячеслав Иванович; Kharuk, Vyacheslav Ivanovich; Рэнсон, Дж.К.; Ranson K.J.

[Text] / K. J. Ranson [et al.] // Remote Sens. Environ. - 2004. - Vol. 93, Is. 3. - P283-295, DOI 10.1016/j.rse.2004.06.019. - Cited References: 38 . - 13. - ISSN 0034-4257РУБ Environmental Sciences + Remote Sensing + Imaging Science & Photographic Technology

Аннотация: Monitoring the dynamics of the circumpolar boreal forest (taiga) and Arctic tundra boundary is important for understanding the causes and consequences of changes observed in these areas. This ecotone, the world's largest, stretches for over 13,400 km and marks the transition between the northern limits of forests and the Southern margin of the tundra. Because of the inaccessibility and large extent of this zone, remote sensing data can play an important role for mapping the characteristics and monitoring the dynamics. Basic understanding of the capabilities of existing space borne instruments for these purposes is required. In this study we examined the use of several remote sensing techniques for characterizing the existing tundra-taiga ecotone. These include Landsat-7, MISR, MODIS and RADARSAT data. Historical cover maps, recent forest stand measurements and high-resolution IKONOS images were used for local ground truth. It was found that a tundra-taiga transitional area can be characterized using multi-spectral Landsat ETM+ summer images, multi-angle MISR red band reflectance images, RADARSAT images with larger incidence angle, or multi-temporal and multi-spectral MODIS data. Because of different resolutions and spectral regions covered, the transition zone maps derived from different data types were not identical, but the general patterns were consistent. (C) 2004 Published by Elsevier Inc.

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

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

[Text] / K. J. Ranson [et al.] // Can. J. Remote Sens. - 2003. - Vol. 29, Is. 2. - P271-285. - Cited References: 32 . - 15. - ISSN 0703-8992РУБ Remote Sensing

Аннотация: As part of a Siberian mapping project supported by the National Aeronautics and Space Administration (NASA), this study evaluated the capabilities of radars flown on the European Remote Sensing Satellite (ERS), Japanese Earth Resources Satellite (JERS), and Radarsat spacecraft and an optical sensor enhanced thematic mapper plus (ETM+) on-board Landsat-7 to detect fire scars, logging, and insect damage in the boreal forest. Using images from each sensor individually and combined, an assessment of the utility of using these sensors was developed. Transformed divergence analysis revealed that Landsat ETM+ images were the single best data type for this purpose. However, the combined use of the three radar and optical sensors did improve the results of discriminating these disturbances.

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Scopus

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

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

[Text] / S. T. Im [et al.] // IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES. Ser. IEEE International Symposium on Geoscience and Remote Sensing (IGARSS) : IEEE, 2003. - 23rd International Geoscience and Remote Sensing Symposium (IGARSS 2003) (JUL 21-25, 2003, TOULOUSE, FRANCE). - P2562-2564. - Cited References: 2 . - 3. - ISBN 0-7803-7929-2РУБ Geosciences, Multidisciplinary + Instruments & Instrumentation + Remote Sensing + Imaging Science & Photographic Technology

Аннотация: Radarsat data validity in classification of Siberian plain taiga ecosystems along the Yenisei River (1GBP transect, 90 E) was analyzed. Six test areas were selected. Those areas represent a variety of the main ecosystem and physical-geographical conditions from the tundra to the southern taiga (forest) zones. The analysis of Radarsat signal amplitude, textural characteristics and digital elevation fused data allowed the detection of 18 onground classes. For the purpose of classification the importance of parameters arrange as follows: relief, signal amplitude, skewness, variance, mean Euclidean distance and kurtosis. The main advantage of the Radarsat data is its ability to detect hydromorphic elements (7 bog types were determined).

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Держатели документа:
Sukachev Inst Forest, Krasnoyarsk, Russia

Доп.точки доступа:
Im, S.T.; Gorodzankina, S.M.; Kharuka, V.I.; Ranson, K.J.

/ 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.

Scopus,
WOS

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.

/ S. T. Im [и др.] // Issled Zemli Kosmosa. - 2004. - Is. 4. - С. 30-41 . - ISSN 0205-9614

Scopus


Доп.точки доступа:
Im, S.T.; Gorodyankina, S.M.; Kharuk, V.I.; Renson, D.K.

/ G. Sun [et al.] // Eurasian Arct. Land Cover and Land Use in a Changing Climate. - 2011. - P53-77, DOI 10.1007/978-90-481-9118-5_4 . -
Аннотация: Monitoring the dynamics of the circumpolar boreal forest (taiga) and Arctic tundra boundary is important for understanding the causes and consequences of changes observed in these areas. Because of the inaccessibility and large extent of this zone, remote sensing data can play an important role for the purposes. In this study, climate-related changes that occurred in the Ary-Mas larch forests (the world's northernmost forest range) in the last three decades of the twentieth century were analyzed. An analysis of Landsat images in 1973 and 2000 has provided evidence for an increase in the closeness of larch forest canopy by 65% and the expansion of larch to the tundra for 3-10 m per year and to areas relatively poorly protected from wind due to topographic features (elevation, azimuth, and slope). It was found that a tundra-taiga transitional area can be characterized using multi-spectral Landsat ETM+ summer images, multi-angle MISR red band reflectance images, RADARSAT images with larger incidence angle, or multi-temporal and multi-spectral MODIS data. Because of different resolutions and spectral regions covered, the transition zone maps derived from different data types were not identical, but the general patterns were consistent. В© 2011 Springer Science+Business Media B.V.

Scopus,
Полный текст

Держатели документа:
Department of Geography, University of Maryland, Greenbelt, MD 20771, United States
Biospheric Sciences Branch, NASA/GSFC, Code 923, Greenbelt, MD 20771, United States
NASA's Goddard Space Flight Center, Greenbelt, MD 20771, United States
V.N. Sukachev Institute of Forest, SB RAS, Academgorodok, 50, 660036 Krasnoyarsk, Russian Federation

Доп.точки доступа:
Sun, G.; Ranson, K.J.; Kharuk, V.I.; Im, S.T.; Naurzbaev, M.M.