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Mapping land cover change in a reindeer herding area of the Russian arctic using Landsat TM and ETM+ imagery and indigenous knowledge

Lookup NU author(s): Dr Meredith Williams


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Much of Russia north of the treeline is grazed by reindeer, and this grazing has materially altered the vegetation cover in many places. Monitoring vegetation change in these remote but ecologically sensitive regions is an important task for which satellite remote sensing is well suited. Further difficulties are imposed by the highly dynamic nature of arctic phenology, and by the difficulty of obtaining accurate official data on land cover in arctic Russia even where such data exist. We have approached the problem in a novel fashion by combining a conventional multispectral analysis of satellite imagery with data on current and historical land use gathered by the techniques of social anthropology, using a study site in the Nenets Autonomous Okrug (NAO). A Landsat-7 ETM+ image from the year 2000 was used to generate a current land cover classification. A Landsat-5 TM image was used to generate a land-cover classification for 1988, taking due account of phenological differences and between the two dates. A cautious comparison of these two classifications, again taking account of possible effects of phenological differences, shows that much of the study area has already undergone a notable transformation to grass-dominated tundra, almost certainly as a result of heavy grazing by reindeer. The grazing pattern is quite heterogeneous, and may have reached unsustainable levels in some areas. Finally, we suggest that this situation is unlikely to be unique to our study area and may well be widespread throughout the Eurasian tundra zone, particularly in the west. © 2003 Elsevier Science Inc. All rights reserved.

Publication metadata

Author(s): Rees WG, Williams M, Vitebsky P

Publication type: Article

Publication status: Published

Journal: Remote Sensing of Environment

Year: 2003

Volume: 85

Issue: 4

Pages: 441-452

ISSN (print): 0034-4257

ISSN (electronic):

Publisher: Elsevier Inc.


DOI: 10.1016/S0034-4257(03)00037-3


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