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      Possible use of remote sensing for reforestation processes in Arctic zone of European Russia

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      Arctic Environmental Research

      Pensoft Publishers

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          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.

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          Most cited references 6

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          Object-based Detailed Vegetation Classification with Airborne High Spatial Resolution Remote Sensing Imagery

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            Comparison of Tasseled Cap-based Landsat data structures for use in forest disturbance detection

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              Development of a UAV-LiDAR System with Application to Forest Inventory

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                Author and article information

                Journal
                Arctic Environmental Research
                AER
                Pensoft Publishers
                2541-8416
                November 02 2018
                November 02 2018
                : 18
                : 3
                : 106-113
                Article
                10.3897/issn2541-8416.2018.18.3.106
                © 2018

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