Mapping of pine forests in the national park “Prielbrusye” based on remote sensing data

At present the most important task is sustainable forest management providing multipurpose inexhaustible forest exploitation, conservation, protection and reforestation. Forestry authorities require current and accurate information on the state of forest ecosystems for sustainable forest management.The study of spatiotemporal forest pattern is impossible without up-to-date cartographic materials. Map-making is feasible using remote information.To form a cartographic model three data sets are applied: Landsat multi-channel scanner photos (at a resolution of 28,5m), radar topographic survey data (SRTM),and field research materials which constitute subsequently a learning sample. The incremental discriminant analysis between remote information and own field research data was made.44 external variables were used for multidimensional analysis, herewith, it is revealed that the key and most distinguishing forest type variables are relief characteristics (altitude above sea level, landform), moisture content in vegetation and soils, general luminance and mountain bedrock. Multidimensional analysis resulted in forming the pattern of pine forest distribution due to which the digital forest map of the Central Caucasus (within the national park “Prielbrusye”) in MapInfo Professional 10.5 batch was modelled. 13 pine forest types of the studied area were mapped. The following groups of forest types are most characteristic for the national park “Prielbrusye”: grass pine forests (40,73 km2), moss pine forests (32,36 km2), birch pine forests (31,58 km2), stony pine forests (31,55 km2). Shrub pine forests are least represented occupying 9,91 km2.Henceforth, it is possible to specify and complement the modelled digital map when obtaining new data on the forest ecosystems of the national park “Prielbrusye” by means of field research results.