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Classification of Sentinel-2 satellite images of the Baikal Natural Territory
I.V. Bychkov 1, G.M. Ruzhnikov 1, R.K. Fedorov 1, A.K. Popova 1, Y.V. Avramenko 1

1 ISDCT SB RAS – Matrosov Institute for System Dynamics and Control Theory of the Siberian Branch of the RAS,
664033, Irkuts, Russia, Lermontova 134

 PDF, 4323 kB

DOI: 10.18287/2412-6179-CO-1022

Pages: 90-96.

Full text of article: Russian language.

Abstract:
The paper considers a problem of classifying Sentinel-2 multispectral satellite images for environmental monitoring of the Baikal Natural Territory (BNT). The specificity of the BNT required the creation of a new set of 12 classes, which takes into account current problems. The set was formed in such a way that the areas corresponding to these classes completely covered the BNT. A training dataset was formed using a web interface based on Sentinel-2 satellite images. The classification of satellite images was carried out using Random Forest algorithms and the ResNet50 neural network. The accuracy of the calculations showed that the classification results can be used to solve actual problems of the Baikal natural territory, in particular, to analyze changes in the forestland, assess the impact of climate change on the landscape, analyze the dynamics of development activities, create farmland inventory, etc.

Keywords:
neural networks, classification, Sentinel-2, remote sensing, image processing.

Citation:
Bychkov IV, Ruzhnikov GM, Fedorov RK, Popova AK, Avramenko YV. Classification of Sentinel-2 satellite images of the Baikal Natural Territory. Computer Optics 2022; 46(1): 90-96. DOI: 10.18287/2412-6179-CO-1022.

Acknowledgements:
The work was financially supported by the Ministry of Science and Higher Education of the Russian Federation under grant No. 075-15-2020-787 for the implementation of a major research project in priority areas of scientific and technological development, "Fundamentals, methods and technologies for digital monitoring and forecasting of the ecological situation of the Baikal Natural Territory".

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