The article deals with the application of remote sensing data in the study of flooding of forests on the example of band boron in Novichikhinsky forestry of the Altai Krai. The results of research are presented, in particular, using the method of object-oriented classification of space images of the earth's surface, which combines the possibility of clustering, qualitatively distinguishes connected objects in the image, and classification with training, which allows to refer the selected objects to pre-defined classes. According to remote sensing data, the areas of flooding and the forest pathology state of the Barnaul belt forest were estimated.
Blaschke T, Johansen K, Tiede D, Weng Q, ed. 2011. Object-based image analysis for vegetation mapping and monitoring. In: Advances in environmental remote Sensing: sensors, algorithms, and applications. CRC Press. p. 1–272. DOI: 10.1201/b10599-13
Fedorova TA. 2011. Forest pest monitoring system of Kurgan region. Bulletin of Kurgan State University 2:46-49.
Gurchenkov АА, Murynin AB, Trekin AN, Ignatiev VYu. 2017. Object-Oriented Classification of Substrate Surface Objects in Arctic Impact Regions Aerospace Monitoring. Herald of the Bauman Moscow State Tech. Univ., Nat. Sci. 3: 135–146. DOI: 10.18698/1812-3368-2017-3-135-146.
Ignatiev VYu, Murynin AB, Trekin AN. 2015. Object oriented space images classification method for impact regions monitoring. Scientific discoveries and achievements. Proc. Int. Sc. Conf.: 176–186.
State Report On the state and environmental protection in the Altai region in 2016. 2017. Barnaul.
Rotanova IN, Koshkarev AV, Medvedev AA. 2014. Use of remote sensing data for digital terrain modelling as part of the regional infrastructure of spatial data. Computational technologies 19(3): 38-47.
Zolotov DV. 2009. Summary of the flora of the Barnaul river basin. Novosibirsk: Nauka.
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