Bergal-Kuvikas Olga, Bindeman Ilya, Chugaev Andrey, Larionova Yulia, Perepelov Alexander, Khubaeva Olga Pleistocene-Holocene Monogenetic Volcanism at the Malko-Petropavlovsk Zone of Transverse Dislocations on Kamchatka: Geochemical Features and Genesis // Pure and Applied Geophysics. 2022. doi: 10.1007/s00024-022-02956-7.
Volkova Maria, Shapiro Nikolay, Melnik Oleg, Mikhailov Valentin, Plechov Pavel, Timoshkina Elena, Bergal-Kuvikas Olga Subsidence of the lava flows emitted during the 2012–2013 eruption of Tolbachik (Kamchatka, Russia): Satellite data and thermal model // Journal of Volcanology and Geothermal Research. 2022. doi: 10.1016/j.jvolgeores.2022.107554.
Гирина О.А., Мельников Д.В., Маневич А.Г., Уваров И.А., Крамарева Л.С. Спутниковый мониторинг эксплозивного извержения 2022 года вулкана Чикурачки (Северные Курилы) // Современные проблемы дистанционного зондирования Земли из космоса. 2022. Т. 19. № 1. С. 302-306. https://doi.org/10.21046/2070-7401-2022-19-1-302-306.
Вулкан Чикурачки находится в северной части хр. Карпинского на о. Парамушир Северных Курил. Его эруптивная деятельность представлена эксплозивными (вулканского типа) и эксплозивно-эффузивными извержениями умеренной силы; состав пород — андезибазальты. Имеются сведения о пятнадцати исторических извержениях вулкана. В работе дано описание извержения в январе – феврале 2022 г. на основании изучения различных спутниковых данных в информационной системе «Дистанционный мониторинг активности вулканов Камчатки и Курил» (VolSatView, http://kamchatka.volcanoes.smislab.ru). Эксплозивное извержение продолжалось трое суток, эксплозии поднимали пепел до 5,5 км над уровнем моря, пепловые шлейфы перемещались до 260 км, в основном на запад, юго-запад и юго-восток от вулкана. Общая площадь пеплопадов в течение извержения превышала 28 тыс. км2, в том числе на суше — 640 км2. Активность вулкана была опасной для местных авиаперевозок.
Chikurachki volcano is located in the northern part of the Karpinsky Ridge on Paramushir Island of the Northern Kuriles. Its eruptive activity is represented by explosive (vulcanian type) and explosive-effusive moderate eruptions; its rock composition is basaltic andesites. Information about fifteen historical eruptions of the volcano is known. The paper describes the eruption in January-February 2022 based on the study of various satellite data in the information system “Remote monitoring activity of Kamchatka and the Kuriles volcanoes” (VolSatView, http://kamchatka.volcanoes.smislab.ru). The explosive eruption continued for three days, the explosions raised ash to 5.5 km above sea level, and ash plumes moved for 260 km mainly to the west, southwest, and southeast of the volcano. The total area of ash falls during the eruption exceeded 28 thousand km2, including 640 km2 on land. Volcanic activity was dangerous for low-flying aircraft.
Belousov Alexander, Belousova Marina, Auer Andreas, Walter Thomas R., Kotenko Tatiana Mechanism of the historical and the ongoing Vulcanian eruptions of Ebeko volcano, Northern Kuriles // Bulletin of Volcanology. 2021. Vol. 83. № 4. P. 1-24. doi: 10.1007/s00445-020-01426-z.
Girina O.A., Loupian E.A., Ozerov A.Yu., Melnikov D.V., Manevich A.G., Petrova E.G. The Activity of Kamchatka Volcanoes and theirs Danger to Human Society (oral report) // JpGU - AGU Joint Meeting 2021: Virtual. 30 May - 06 July, 2021, Japan, Tokyo. 2021. № C001019.
There are 30 active volcanoes in the Kamchatka, and several of them are continuously active. In the XX-XXI centuries 17 volcanoes of Kamchatka erupted. During this time, 183 volcanic eruptions occurred, including three catastrophic eruptions (Ksudach, 1907; Bezymianny, 1956; Sheveluch, 1964). Strong explosive eruptions of volcanoes were the most dangerous for human society because they produce in a few hours or days to the atmosphere till 2-3 cubic kilometers of volcanic products. Ash plumes and the clouds, depending on the power of the eruptions, the strength and wind speed, to traveled thousands of kilometers from the volcanoes for several days. Any territory of the Kamchatka Peninsula has repeatedly been exposed to ash falls, the thickness of ash in settlements was from less than 1 mm to 4-5 cm. Strong explosive eruptions of volcanoes Sheveluch, Klyuchevskoy, Bezymianny, Kizimen, Karymsky, Zhupanovsky, Avachinsky, Kambalny were the most dangerous for air travel not only over Kamchatka, but also hundreds of kilometers away from the peninsula.
The strong explosive and effusive eruptions of Sheveluch, Klyuchevskoy, Bezymianny, Kizimen and the other were often accompanied by the formation of hot mud flows (lahars), which sometimes disrupted transport communications (roads, bridges) of nearby settlements.
Scientists of KVERT monitor Kamchatkan volcanoes since 1993. Thanks to satellite monitoring of volcanoes carried out by KVERT, several explosive eruptions were predicted in the XXI century, and early warnings were made to the population about possible ashfalls in settlements and about hazard to aviation.
Girina O.A., Loupian E.A., Sorokin A.A., Romanova I.M., Melnikov D.V., Manevich A.G., Nuzhdaev A.A., Bartalev S.A., Kashnitskii A.V., Uvarov I.A., Korolev S.P., Malkovsky S.I., Kramareva L.S. Information Technologies for the Analyzing of Kamchatka and the Kuril Islands Volcanoes Activity in 2019-2020 // Short Paper Proceedings of the VI International Conference on Information Technologies and High-Performance Computing (ITHPC 2021), Khabarovsk, Russia, September 14-16, 2021. Khabarovsk: CEUR-WS.org. 2021. Vol. 2930. P. 112-118.
The work is devoted to the activity analysis of Kamchatka and the Kuril Islands volcanoes in 2019-2020.The activity of the volcanoes was estimated based on the processing of data from daily satellite monitoring carried out using the information system “Remote monitoring of Kamchatkan and the Kuriles volcanoes activity (VolSatView)”. The activity of the Kamchatka and the Kuril Islands volcanoes considered based on the analysis of their thermal anomalies. Analysis of the characteristics of thermal anomalies over volcanoes was carried out in KVERT IS. Analysis of the temperature of thermal anomalies of volcanoes in the Kuril - Kamchatka region in 2019-2020 shows a significantly higher activity of the Kamchatka volcanoes in comparison with the Kuril volcanoes.
Horváth Á, Carr J.L., Girina O.A., Wu D.L., Bril A.A., Mazurov A.A., Melnikov D.V., Hoshyaripour G.A., Buehler S.A. Geometric estimation of volcanic eruption column height from GOES-R near-limb imagery – Part 1: Methodology // Atmospheric Chemistry and Physics. 2021. Vol. 21. Vol. 16. P. 12189-12206. https://doi.org/10.5194/acp-21-12189-2021, 2021.
A geometric technique is introduced to estimate the height of volcanic eruption columns using the generally discarded near-limb portion of geostationary imagery. Such oblique observations facilitate a height-by-angle estimation method by offering close-to-orthogonal side views of eruption columns protruding from the Earth ellipsoid. Coverage is restricted to daytime point estimates in the immediate vicinity of the vent, which nevertheless can provide complementary constraints on source conditions for the modeling of near-field plume evolution. The technique is best suited to strong eruption columns with minimal tilting in the radial direction. For weak eruptions with severely bent plumes or eruptions with expanded umbrella clouds the radial tilt/expansion has to be corrected for either visually or using ancillary wind profiles. Validation on a large set of mountain peaks indicates a typical height uncertainty of ±500 m for near-vertical eruption columns, which compares favorably with the accuracy of the common temperature method.
Horváth Á, Girina O.A., Carr J.L., Wu D.L., Bril A.A., Mazurov A.A., Melnikov D.V., Hoshyaripour G.A., Buehler S.A. Geometric estimation of volcanic eruption column height from GOES-R near-limb imagery – Part 2: Case studies // Atmospheric Chemistry and Physics. 2021. Vol. 21. Vol. 16. P. 12207-12226. https://doi.org/10.5194/acp-21-12207-2021.
In a companion paper (Horváth et al., 2021), we introduced a new technique to estimate volcanic eruption column height from extremely oblique near-limb geostationary views. The current paper demonstrates and validates the technique in a number of recent eruptions, ranging from ones with weak columnar plumes to subplinian events with massive umbrella clouds and overshooting tops that penetrate the stratosphere. Due to its purely geometric nature, the new method is shown to be unaffected by the limitations of the traditional brightness temperature method, such as height underestimation in subpixel and semitransparent plumes, ambiguous solutions near the tropopause temperature inversion, or the lack of solutions in undercooled plumes. The side view height estimates were in good agreement with plume heights derived from ground-based video and satellite stereo observations, suggesting they can be a useful complement to established techniques.
Korolev S.P., Sorokin A.A., Urmanov I.P., Kamaev A., Girina O.A. Classification of Video Observation Data for Volcanic Activity Monitoring Using Computer Vision and Modern Neural NetWorks (on Klyuchevskoy Volcano Example) // Remote Sensing. 2021. Vol. 13. Vol. 23. № 4747. P. 1-20. https://doi.org/10.3390/rs13234747.
Currently, video observation systems are actively used for volcano activity monitoring. Video cameras allow us to remotely assess the state of a dangerous natural object and to detect thermal anomalies if technical capabilities are available. However, continuous use of visible band cameras instead of special tools (for example, thermal cameras), produces large number of images, that require the application of special algorithms both for preliminary filtering out the images with area of interest hidden due to weather or illumination conditions, and for volcano activity detection. Existing algorithms use preselected regions of interest in the frame for analysis. This region could be changed occasionally to observe events in a specific area of the volcano. It is a problem to set it in advance and keep it up to date, especially for an observation network with multiple cameras. The accumulated perennial archives of images with documented eruptions allow us to use modern deep learning technologies for whole frame analysis to solve the specified task. The article presents the development of algorithms to classify volcano images produced by video observation systems. The focus is on developing the algorithms to create a labelled dataset from an unstructured archive using existing and authors proposed techniques. The developed solution was tested using the archive of the video observation system for the volcanoes of Kamchatka, in particular the observation data for the Klyuchevskoy volcano. The tests show the high efficiency of the use of convolutional neural networks in volcano image classification, and the accuracy of classification achieved 91%. The resulting dataset consisting of 15,000 images and labelled in three classes of scenes is the first dataset of this kind of Kamchatka volcanoes. It can be used to develop systems for monitoring other stratovolcanoes that occupy most of the video frame.