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Siberian Journal of Forest Science

2019 year, number 6


A. A. Karpov1,2, N. R. Pirtskhalava-Karpova1, A. P. Bogdanov1,2, R. A. Aleshko1,2, V. V. Voronin2
1Northern Federal University named after M. V. Lomonosov, Severnaya Dvina Emb., 17, Arkhangelsk, 163002 Russian Federation
2Northern Research Institute of Forestry, Nikitov str., 13, Arkhangelsk, 163062 Russian Federation
Keywords: дистанционные методы мониторинга, лесовосстановление, вегетационный индекс, SWVI, NBR, NDVI, Google Earth Engine, Архангельская область, remote sensing methods of monitoring, reforestation, vegetation indices, SWVI, NBR, NDVI, Google Earth Engine, Arkhangelsk Oblast


Assessment of forest regeneration using remote sensing data is a priority scientific research topic worldwide today. Threshold values for successful reforestation can be defined using multi-temporal satellite scenes and indices for analysis of vegetation on cutting and burned areas. The analysis of successful reforestation has practical value for Russian government organizations for transferring burned and cutting lands to forest cover land. The rate of reforestation depends on climate, soil conditions in the region of studies. Collection of field data and the studies were carried out in northern and middle taiga of Arkhangelsk Oblast. This territory belongs to boreal forest. Calculations of spectral indices for each research object were made using multi-temporal scenes for 20 years based on Google Earth Engine platform. Optimal spectral index was selected based on the analysis of collected data. The optimal threshold values of the index for transferring pixel of satellite imagery to forest cover land were found using this data. Optimal spectral index for transferring non-forest cover to forest cover land SWVI was selected. The optimal threshold value for transfer to forest cover land equals 80 % recovery of the index after a disturbance in forest cover. Method for transferring land to forest cover land was developed based on analysis of dynamic of the spectral index. The result was the spatial layer of transferring land to forest cover land in 2018 on the territory of Severodvinsk and Onega forestry district of Arkhangelsk Oblast.