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Assessment of changes in composition and spatial organization of forests is particularly important for areas with a high level of anthropogenic impact. The study of the spatial organization of the forest cover is associated with the selection of thematic classes and their cartographic mapping. In recent years, the classification of vegetation has become an effective tool not only for describing biodiversity, but is used as an important tool for understanding the relationship between vegetation dynamics and environmental factors, the prediction and management of biodiversity. The possibilities of remote sensing and geo-information technologies require special standards for the classification of vegetation cover. The purpose of this work is to assessment the damage from metallurgical plant to forest ecosystems and to create the map the coenotic diversity of the cool forests. The modern diversity was assessed by the example of the model region with an area of 8400 km2 in the central part of the Murmansk Region, which includes the territory of the Lapland Nature Reserve and a large part of Khibiny mountains area. The eco-phytocoenotic classification (EPC) for assessing the typological diversity of vegetation cover was used. As a result of classification, 47 typological units at the ranks of groups and association classes that characterize the diversity of vegetation (forests, elfin woodland, marshes, and mountain tundra) were identified. Statistical methods and GIS technologies based on joint processing of geobotanical data, satellite information (Landsat 4, 5 and 7, GeoCover TM and ETM) and digital elevation models (DEM) were used to assess the spatial differentiation of forest cover. The technique of digital mapping was carried out by interpolation of vegetation classes at the upper scale levels by comparing them with remote sensing data and DEM based on the training sample. Analyses of spatial distribution of plant communities using field data, RSD, DEM, and statistical methods made it possible to consider their composition and structure with consideration of successional status and anthropogenic impacts. Altitudinal gradient of mountain ranges, anthropogenic disturbance, and the natural dynamics of plant communities at different successional stages were the main factors affecting spatial differentiation of vegetation cover in the model area. Fires and air pollution emissions from smelter were among the types of anthropogenic impacts that prevail in this region. Analysis of the physical content of discriminant axes showed that approximately 23% of the study area is covered by anthropogenically-modified vegetation. The overall relative quality of the discriminant analysis was 76%.