Software-algorithmic complex of forecasting the dynamics of arctic lakes in Russia based on satellite images and entropy-randomized approach

The article is devoted to the problem of predicting the evolution of thermokarst lakes in permafrost zones as intensive sources of natural emissions of greenhouse gases into the atmosphere in the Arctic territories. Goal of the work. The purpose of the work was to consider the issues of creating a software-algorithmic complex for predicting the spatio-temporal dynamics of lakes in the Russian Arctic based on methods and algorithms of randomized machine learning.