Based on computer vision and machine learning methods, algorithms have been developed to classify images from fixed video cameras, as well as detect signs of volcanic activity in them. The results of testing the developed algorithms are presented using the example of observation data on the Klyuchevskoy and Sheveluch volcanoes. It is shown that the proposed solutions can be used for operational and retrospective monitoring of volcanic activity.

Представлены первые результаты применения спутниковых данных VIIRS Nightfire для мониторинга извержения вулкана Крашенинникова, начавшегося в августе 2025 г. За период август 2025 – февраль 2026 гг. оценены динамика извержения, температура лавовых потоков и их объем. Общий объем излившейся лавы ~0.13 км3, максимальная скорость истечения – до ~97 м3/с.

The volcanoes of Kamchatka are the most active in the world. Annually, from 3 to 7 volcanoes produce eruptions, during which the explosions eject ash to 10−15 km above sea level, and ash clouds spread thousands of kilometers from volcanoes. Strenuous volcanic activity could cause ash falls in towns and settlements, destruction of forests and communications. Ash clouds and plumes pose a serious threat to the present-day jet aviation. Since 1993, the Kamchatka Volcanic Eruption Response Team (KVERT) has conducted daily monitoring of Kamchatka volcanoes to mitigate volcanic hazards to airline operations and population. Since 2014, satellite monitoring of volcanoes is carried out by KVERT scientists using the VolSatView information system that since 2016 has utilized data from Himawari-8 geostationary satellite. The system has created special tools that allow us to work with promptly received data, as well as analyze series of long-term observations. Using data from Himawari-8, as well as the tools implemented in VolSatView to work with them, enables to: significantly raise the efficient response to detection of explosive events in the region; identify the onset of eruptive events with an accuracy of 10 minutes or less; track and forecast all changes in the dynamics of volcanic activity, including the near onset of strong explosive events. The paper describes the technology features for integrating Himawari-8 data into VolSatView and the main possibilities of working with them, implemented now
in the system.

SIGMA-3D software package of structural interpretation is an effective tool for the automated three-dimensional modeling while studying magnetic anomalies created by underwater volcanoes. With the help of this software package submarine volcanoes Grigorieva, Krylatka, and Yubileiny, located in the Kurile island arc, have been studied.