Abstract
This article considers the possibility of using remote sensing to monitor reforestation as exemplified in the Severodvinsk and Onezhsk forestry districts of the Arkhangelsk region of Russia’s Arctic zone. Remote sensing makes use of medium spatial resolution satellite images and high resolution unmanned aerial vehicle (UAV) images. In the course of work on the project, a preliminary method was developed for reforesting land previously subjected to cutting, fire, or windfall. Steps include detecting a reduction in forest cover and collecting field data through the use of UAVs to create a training set, which is used to classify satellite images according to the two classes of ‘restored’ or ‘not restored’. Various data processing tools are used to perform these steps. The Tasseled Cap multi-channel satellite image transformation method is employed as a tool for detecting a reduction in forest cover and analysing reforestation. The k-nearest neighbour algorithm is employed to classify satellite images. This article provides a step-by-step algorithm for monitoring and an assessment is provided of the situation in relation to forest regeneration in the Severodvinsk and Onezhsk forestry districts. The work carried out has shown that it is possible to use UAV images to monitor forest recovery, which is of significant importance for the conditions of the Arctic zone of European Russia.
Highlights
It is of great importance to monitor forest regeneration in the Arctic zone in a changing climate and while the areas are under active development, especially when these factors are shown to have an effect on forests with low reforestation potential
– creating a layer of forest cover reduction; – carrying out field work, which includes establishing test plots and surveying the territory with a unmanned aerial vehicle (UAV); – analysing the information collected in the field and creating a training sample for the transfer of forest land to forested areas in accordance with Earth remote sensing (ERS) data; – creating a layer of land to transfer to forest cover
The use of UAVs made it possible to cover a large number of trial plots. 3037 trial plots were built for reforestation analysis with the help of UAVs
Summary
It is of great importance to monitor forest regeneration in the Arctic zone in a changing climate and while the areas are under active development, especially when these factors are shown to have an effect on forests with low reforestation potential. The introduction of remote reforestation monitoring will make it possible to monitor a large area and receive timely and relevant information. The use of remote sensing to assess the successfulness of reforestation has not been widely studied. There are examples in the existing literature of the use of multi-temporal images obtained from the Landsat satellite to monitor reforestation (Krankina et al 2005; Vorobev et al 2016). The use of these images with the application of spectral brightness or index characteristics derived therefrom point to the possibility of obtaining information about reforestation processes in disturbed areas (Maltese et al 2005). It is possible to estimate with a high degree of accuracy the success of woody plant regeneration with the help of spectral characteristics for plantations closer to the age of 15 years; this conclusion was reached during studies of the regeneration of Douglas-fir in the western part of the Oregon Cascade Mountains, USA (Fiorella and William 2009)
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