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, 2017, Vol. 14, No. 2, pp. 72-83

Analysis of projective cover and biomass storage of epigeous lichens in vegetation cover of Pasvik Nature Reserve

V.V. Elsakov 1 , V.M. Shchanov 1 , N.V. Polikarpova 2 
1 Institute of Biology, Komi Science Centre UB RAS, Syktyvkar, Russia
2 Pasvik State Nature Reserve, Rayakoski, Murmansk Region, Russia
Accepted: 01.03.2017
DOI: 10.21046/2070-7401-2017-14-2-72-83
The work presents the results of analysis of satellite images of different resolutions (World View 2, Landsat) and instrumental field investigations meant to model projective cover (PC) and total biomass (TB) of ground lichens in vegetation cover of Pasvik Nature Reserve. The models were shaped using multivariate linear regression methods (MLR) in combination with field measurement data. The average PC in the vegetation cover was 6.4% (0.9–21.5%). The PC values of lichens in the reserve obtained by means of the received model were 6.3 times lower than the values calculated using only classes of lichen communities in the Landsat relevant classification. The lowest differences were traced for landscape-geobotanical sites with low representation of lichen classes and low PC of lichens in the ground cover (less than 5%). Sites dominated by mires demonstrated minimal differences between the compared values – avg. 1.1 times (0.5–1.9). For the other types of communities, the use of relevant classification (map of vegetation) for calculation the area values increased the PC of ground lichens by 6.8 times for mountain tundra (5.6–8.1 times) and by 8.0 times for forests (2.5–19.8 times). The obtained results allowed to update and extrapolate the instrumental data to the whole protected territory. The TB model of lichens assessed the total storage of lichen thalli in the communities of the reserve in 970 tons with the average density of 512 kg per ha throughout the territory (20.9–1962 kg per ha). A comparison of the obtained results with independent expert data (using deer capacity value) demonstrated the model’s overall underestimation by 18.2%. It highlights the importance of using component analysis methods in quantitative calculations of resource characteristics of phytocoenoses.
Keywords: remote sensing methods, epigeous lichens biomass storage and projective cover, vegetation cover, Pasvik Nature Reserve
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