BIO Web Conf.
Volume 38, 2021Northern Asia Plant Diversity: Current Trends in Research and Conservation 2021
|Number of page(s)||5|
|Published online||28 October 2021|
Vegetation cover analysis of the mountainous part of north-eastern Siberia by means of geoinformation modelling and machine learning (basic principles, approaches, technology and relation to geosystem science)
Institute of Natural Sciences, North-Eastern Federal University, Yakutsk, Russia
2 Institute for Biological Problems of Cryolithozone, SB RASciences, Yakutsk, Russia
3 Aix-Marseille University, UMR ESPACE CNRS, Aix-en-Provence, France
* Corresponding author: firstname.lastname@example.org
For the first time, the geoinformation modelling and machine learning approaches have been used to study the vegetation cover of the mountainous part of North-Eastern Siberia – the Orulgan medium-altitude mountain landscape province. These technologies allowed us to distinguish a number of mapping units that were used for creation and analysis of 1:100 000 scale vegetation map of the interpreted key area. Based on the studies, we decided upon the basic principles, approaches and technologies that would serve as a methodology basis for the further studies of vegetation cover of the large region. Relief, slope aspect, genetic types of sediments, and moisture conditions were selected as supplementary factors to the vegetative indices for differentiation of both plant communities and vegetation map units.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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