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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2016, Vol. 13, No. 5, pp. 167-191

Definition of factors of spatial variation in vegetation using RSD, DEM and field data by example of the central part of Murmansk Region

M.Yu. Puzachenko 1 , T.V. Chernenkova 2 
1 Institute of Geography RAS, Moscow, Russia
2 Centre for Forest Ecology andjavascript:; Production RAS, Moscow, Russia
Accepted: 18.07.2016
DOI: 10.21046/2070-7401-2016-13-5-167-191
The work is devoted to the identification of regularities of formation of the typological diversity of vegetation through the use of digital elevation models (DEM), field and remote sensing data (RSD). The study area is located in the central part of Murmansk Region and covers the greater part of the Lapland Nature Reserve, the Khibiny Massif, as well as the neighborhood of a metallurgical plant. The results of stepwise discriminant analysis demonstrated the possibility to identify the relatively large number of natural and anthropogenic damaged types of plant communities at the level of groups of associations. The map of actual vegetation of the study region (scale 1:200 000) was created. The analysis of the obtained map showed that about 23% of the study area were anthropogenically transformed plant communities of varying degrees of transformation. The ecologo-phytocoenotic approach, used for the classification, allows to reflect in the legend of the map the information about natural and transformed plant communities of different ecological condition. The use of different spatial data sources, along with the use of methods of statistical analysis, makes it possibile not only to develop a map of vegetation cover, but also to highlight key driving forces at the regional level, among which the main ones are the climatic altitude gradients, water supply conditions, anthropogenic transformations and natural self-development of plant communities.
Keywords: forest cover, diversity, ecosystem variation, mapping, classification, remote sensing data, digital elevation models, Murmansk Region
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