SOFTWARE-ALGORITHMIC COMPLEX OF FORECASTING THE DYNAMICS OF ARCTIC LAKES IN RUSSIA BASED ON SATELLITE IMAGES AND ENTROPY-RANDOMIZED APPROACH

• Published in: Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & Radioelectronics
• Main Authors: Сокол, Евгений Сергеевич, Тогачев, Александр Алексеевич, Попков, Алексей Юрьевич, Дубнов, Юрий Андреевич, Полищук, Владимир Юрьевич, Попков, Юрий Соломонович, Мельников, Андрей Витальевич, Полищук, Юрий Михайлович
• Other Authors: The work was supported by grant of Russian scientific fund for the project No. 22-11-20023, Работа проводилась при финансовой поддержке гранта Российского научного фонда по проекту № 22–11-20023
• Format: Article in Journal/Newspaper
• Language: Russian
• Published: South Ural State University 2023
• Subjects: machine learning; randomized model; software-algorithmic complex; forecasting; thermokarst lakes; greenhouse gases; машинное обучение; рандомизированная модель; программно-алгоритмиче¬ский комплекс; прогнозирование; термокарстовые озера; парниковые газы; Arctic; permafrost; Thermokarst; термокарст*
• Online Access: https://vestnik.susu.ru/ctcr/article/view/13708; https://doi.org/10.14529/ctcr230402

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. Materials and methods. For forecasting, time series of satellite measurements of the areas of thermokarst lakes in the Arctic zone of Russia and data on the average annual temperature and annual precipitation obtained on the basis of the ERA-5, ERA-Interim, etc. reanalysis systems are used for forecasting. Methods of entropy-randomized dynamics modeling are used fields of thermokarst lakes, allowing to predict changes in the areas of lakes in the Arctic zone. For the software implementation of a complex for predicting the evolution of the area of thermokarst lakes, modern geographic information systems are used. Results. The architecture of the software-algorithmic complex has been developed, based on the use of entropy-randomized modeling algorithms. The software-algorithmic forecasting complex makes it possible to train and test the model based on available historical data on the dynamics of the area of thermokarst lakes and climate changes in the Russian Arctic. Conclusion. The implementation of a software package based on the NextGIS Web geographic information system allows you to include forecasting applications in Python. The developed software package can be used in assessing and forecasting the dynamics of greenhouse gas emissions from lakes, which influence changes in air temperature in the northern regions. Статья посвящена проблеме прогнозирования эволюции термокарстовых озер в зонах мерзлоты как интенсивных источников природной эмиссии парниковых газов в атмосферу на арктических территориях. Цель работы. Целью работы является рассмотрение ...