ASSESSMENT OF THE VEGETATION COVER CONDITIONS FOR THE CENTRAL PART OF THE MURMANSK REGION BASED ON FIELD AND REMOTE SENSING DATA

Michael Puzachenko; Tatyana Chernenkova

doi:10.24057/2071-9388-2012-5-3-4-13

ASSESSMENT OF THE VEGETATION COVER CONDITIONS FOR THE CENTRAL PART OF THE MURMANSK REGION BASED ON FIELD AND REMOTE SENSING DATA

Michael Puzachenko, Tatyana Chernenkova

https://doi.org/10.24057/2071-9388-2012-5-3-4-13

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Abstract

Research of the forest ecosystems dynamics of northwestern Russia on the Kola Peninsula (the Imandra Lake watershed) under the influence of strong anthropogenic impacts caused by the industrial complex “Severonikel” over the last 70 years was carried out. Statistical analysis was used for comparison and interpolation of field data, multispectral remote sensing data (MRSD), and digital elevation model (DEM). From this analysis, the classification of natural and anthropogenic classes of the vegetation and land cover was developed; the model highlighted the key driving forces behind the spatial differentiation of vegetation (altitudinal climate gradients, anthropogenic disturbance, water supply, and development of the natural vegetation communities). In addition, the map of the current vegetation conditions at a scale of 1:100 000 was created. This map characterizes the large part of the Lapland Nature Reserve, the territory of the Khibiny mountains, as well as the polluted area near the metallurgical plant.

Keywords

forest ecosystems dynamics, anthropogenic disturbance, discriminate analysis

About the Authors

Michael Puzachenko

Russian Federation
Senior scientist, Institute of Geography of the Russian Academy of Sciences, Moscow, Russia, Staromonetny str., 29, 119017

Tatyana Chernenkova

Russian Federation
Leading scientist, Centre for Forest Ecology and Production of the Russian Academy of Sciences, Moscow, Russia, Profsoyuznaya str., 84/32, 117997

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For citation:

Puzachenko M., Chernenkova T. ASSESSMENT OF THE VEGETATION COVER CONDITIONS FOR THE CENTRAL PART OF THE MURMANSK REGION BASED ON FIELD AND REMOTE SENSING DATA. GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY. 2012;5(3):4-13. https://doi.org/10.24057/2071-9388-2012-5-3-4-13