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)

Abstract

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.