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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2018, Vol. 15, No. 1, pp. 89-100

Improving forest monitoring by using cloud technologies as an element of sustainable forest management

A.P. Bogdanov 1, 2 , A.A. Karpov 1, 2 , N.A. Demina 1 , R.A. Aleshko 2 
1 Northern Research Institute of Forestry, Arkhangelsk, Russia
2 Northern (Arctic) Federal University, Arkhangelsk, Russia
Accepted: 27.11.2017
DOI: 10.21046/2070-7401-2018-15-1-89-100
At the present time, forest monitoring is conducted in various ways. The main goal of forest monitoring that uses remote sensing technologies is to assess the state of the forest. The assessment of reforestation is also one of the tasks of forest monitoring on the basis of this form of technology. Satellite monitoring allows assessing forest recovery in clean cut and burnt areas for their conversion into forest areas with successful reforestation and appointment of cleaning cutting in the future. To distinguish forest cutting, burnt areas and the assessment of reforestation, it is possible to use spectral indices. In this article, an analysis of dynamic patterns of indices SWVI, NBR, and NDVI in forests under negative effect (i.e. cutting, burnt areas) was conducted. Landsat 5 and 8 satellite images were used for the analysis of forest environment changes at different times. The calculation and analysis of the data was performed using the Google Earth Engine platform. This platform uses cloud technology that allows automatic and accelerated processing of large amounts of data and satellite images. Furthermore, field studies of forest areas exposed to low fire and clean cutting were conducted in the framework of this research. Sample areas were located in the Obozerskoe and Krasnoborskoe forests of the Arkhangelsk region. This research showed that it is possible to use spectral indices to monitor and assess reforestation.
Keywords: remote monitoring methods, decryption, multispectral space imagery, forest pathological condition, vegetation index, SWVI; NBR, NDVI, Google Earth Engine; Arkhangelsk region
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