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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, 2015, Vol. 12, No. 3, pp. 87-97

Satellite methods for the analysis of changes in lichen cover in vegetation communities of Pasvik Nature Reserve

V.V. Elsakov1 , N.V. Polikarpova2 
1 Institute of Biology, Komi Science Centre UrD RAS, Syktyvkar, Russia
2 Pasvik State Nature Reserve, Rayakoski, Murmansk Region, Russia
The work presents an analysis of changes in plant communities at Pasvik Nature Reserve (established in 1992) for the period of 1984–2014 based on Landsat satellite data. The results of field research and geobotanical satellite maps allowed estimating the contribution of the dominant vegetation communities of the reserve area. A developed lichen cover is recorded on 33,6% of the territory, 28,8% of which is comprised of pine forest. Spectrometric measurements of different lichens demonstrate the peculiar nature of lichen thalli reflectance spectra, which is different from brightness characteristics of vascular plants. All spectra of model lichens can be grouped into three classes. Reflection curves are significantly affected by the moisture content of thalli; the maximum absorption is observed at a moisture content in the range of 100–150% of the air-dry weight. The analysis of spectral perpendicular vegetation index (PVI) has shown, that in the considered time period, the most part of the reserve territory has experienced a weak positive growth of green phytomass (a change from 0 to 0,2 PVI per year was recorded on 58,6% of the territory). In the lichen communities, overall growth exceeded degradation. In the areas of permanent pasture within the Norwegian reindeer pastures, a significant decline was observed reflected in weaker growth and negative trend of PVI.
Keywords: trends of vegetation changes, Pasvik Nature Reserve, spectrometric measurements, lichens, index PVI, multi-temporal Landsat composites
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