MAPPING OF THE VEGETATION COVER OF THE PERM REGION BASED ON LANDSAT SATELLITE IMAGES

Abstract

The paper deals with the methodology and results of Landsat-based vegetation cover mapping for the Perm region. Initial Landsat images were obtained in 2016–2020. The map building technique is based on the supervised classification of satellite images and subsequent post-processing. This technique involves the use of a number of additional sources, in particular, the results of global-Landsat-based mapping of forest disturbances, water surface, and arable lands, as well as reforestation areas on abandoned agricultural lands. As a result, a map with a spatial resolution of 30 m (which corresponds to a scale of 1:100,000) has been created. The map legend includes 19 thematic classes, 11 of them contain information on forest vegetation. The accuracy assessment of the obtained data was carried out with the use of a MODIS-based map of the vegetation cover of Russia and also forest inventory data on two forestries of the Perm region. The highest classification accuracy is typical for dark-coniferous and pine forests (it is about 70% according to the map of the vegetation cover of Russia, and up to 75% according to the forest inventory data). Deciduous forests are recognized with the lowest accuracy since, according to the classification results, they were partly categorized as mixed forests (with a predominance of deciduous species). The practical use of the created map of the vegetation cover may include estimation of long-term changes for individual vegetation classes (in particular, for intact forest landscapes), or various calculations based on the species composition and age structure of the forests. The compiled map of the vegetation cover of the Perm region is available at https://figshare.com/s/98d29e83d1f2039b2528.