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

[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.

WOS,
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] / V. I. Kharuk [et al.] // Int. J. Remote Sens. - 2003. - Vol. 24, Is. 1. - P23-37, DOI 10.1080/0143116021000021143. - Cited References: 30 . - 15. - ISSN 0143-1161РУБ Remote Sensing + Imaging Science & Photographic Technology

Аннотация: In this paper NOAA AVHRR data acquired at the Sukachev Institute of Forest in Siberia, Russia is evaluated for forest management mapping applications. First a classification of the entire 1000 km x 3000 km transect was performed, but was found to be too general to be of value. More useful interpretation procedures require a landscape-ecological approach. This means that computer classification should be made separately for segments of territory based ecologically distinct regions. This segmentation of the transect into ecological regions was found to improve the level of detail available in the classification. Using this approach AVHRR data were found to be adequate for small scale mapping at the level of vegetation types or plant formations. A limited study using AVHRR data for classification of mountainous regions showed that AVHRR-derived maps were more detailed than existing landscape maps. AVHRR derived classifications also compared favourably to larger scale forest management maps of softwood and hardwood forests. Current forest management in Siberia relies on very small-scale inventory maps. Thus, there is a potential role for AVHRR (or Terra) data for northern Siberian forest monitoring. The southern forests of the Yenisey meridian (below the 57th parallel) are less uniform due to considerable human activity, and NOAA/AVHRR data will play a subordinate role in its monitoring.

Полный текст,
WOS,
Scopus

Держатели документа:
Sukachev Inst Forest, Krasnoyarsk, Russia
NASA, Goddard Space Flight Ctr, Biospher Sci Branch, Greenbelt, MD 20771 USA

Доп.точки доступа:
Kharuk, V.I.; Ranson, K.J.; Burenina, T.A.; Fedotova, E.V.