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Kopylova G.N., Boldina S.V. Groundwater Pressure Changes Due to Magmatic Activation: Case Study of The E-1 Well, Kamchatka Peninsula, Russia // Geothermal Volcanology Workshop 2020. September 03-09, 2020, Petropavlovsk-Kamchatsky, Institute of Volcanology and Seismology. 2020.
Kopylova G.N., Boldina S.V. On the Relationships of Water-Level Variations in the E-1 Well, Kamchatka to the 2008–2009 Resumption of Activity on Koryakskii Volcano and to Large (M ≥ 5) Earthquakes // Journal of Volcanology and Seismology. 2012. Vol. 6. № 5. P. 312-328. doi: 10.1134/S074204631205003X.
   Аннотация
Abstract—We discuss the water!level variations in the E!1 well for the time period between May 2006 and
2010, inclusive. A trend towards an increasing level at an abnormally high rate occurred from mid!2006 to
December 2009. This increase is regarded as the response of the aquifer of gas!saturated ground water that
exists in the volcanogenic–sedimentary deposits of the Avacha volcano!tectonic depression to volumetric
strain changes during the precursory period and the occurrence of a swarm of small earthquakes ( = 8.3)
in the area of Koryakskii Volcano and to its phreatic eruption. We estimated the volumetric compression as
Δε = –(4.1 × 10–6–1.5 × 10–5) from the amplitude of water!level rise using the elastic parameters of the wa!
ter!saturated rocks. While the strain source was active, we observed a decreasing sensitivity of the hydrologic
regime in the well to the precursory processes before large (M ≥ 5.0) tectonic earthquakes.
Korolev S.P., Romanova I.M., Girina O.A., Sorokin A.A., Malkovsky S.I., Urmanov I.P. Software platform for volcano video monitoring // 10th Biennual workshop on Japan-Kamchatka-Alaska subduction processes (JKASP-2018). Petropavlovsk-Kamchatsky, Russia, August 20-26. Petropavlovsk-Kamchatsky: IVS FEB RAS. 2018. P. 117-119.
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.
   Аннотация
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.
Korolev S.P., Urmanov I.P., Kamaev A., Girina O.A. Parametric Methods and Algorithms of Volcano Image Processing / Software Engineering Perspectives in Intelligent Systems. Advances in Intelligent Systems and Computing. Cham: Springer. 2020. Vol. 1295. P. 253-263. https://doi.org/10.1007/978-3-030-63319-6_22.
   Аннотация
A key problem of any video volcano surveillance network is an inconsistent quality and information value of the images obtained. To timely analyze the incoming data, they should be pre-filtered. Additionally, due to the continuous network operation and low shooting intervals, an operative visual analysis of the shots stream is quite difficult and requires the application of various computer algorithms. The article considers the parametric algorithms of image analysis developed by the authors for processing the shots of the volcanoes of Kamchatka. They allow automatically filtering the image flow generated by the surveillance network, highlighting those significant shots that will be further analyzed by volcanologists. A retrospective processing of the full image archive with the methods suggested helps to get a data set, labeled with different classes, for future neural network training.
Korolev S.P., Urmanov I.P., Sorokin A.A., Girina O.A. Detecting Volcano Thermal Activity in Night Images Using Machine Learning and Computer Vision // Remote Sensing. 2023. Vol. 15. Vol. 19. № 4815. https://doi.org/10.3390/rs15194815.
   Аннотация
One of the most important tasks when studying volcanic activity is to monitor their thermal radiation. To fix and assess the evolution of thermal anomalies in areas of volcanoes, specialized hardware-thermal imagers are usually used, as well as specialized instruments of modern satellite systems. The data obtained with their help contain information that makes it relatively easy to track changes in temperature and the size of a thermal anomaly. At the same time, due to the high cost of such complexes and other limitations, thermal imagers sometimes cannot be used to solve scientific problems related to the study of volcanoes. In the current paper, day/night video cameras with an infrared-cut filter are considered as an alternative to specialized tools for monitoring volcanoes’ thermal activity. In the daytime, a camera operated in the visible range, and at night the filter was removed, increasing the camera’s light sensitivity by allowing near-infrared light to hit the sensor. In that mode, a visible thermal anomaly could be registered on images, as well as other bright glows, flares, and other artifacts. The purpose of this study is to detect thermal anomalies on night images, separate them from other bright areas, and find their characteristics, which could be used for volcano activity monitoring. Using the image archive of the Sheveluch volcano as an example, this article presents the results of developing a computer algorithm that makes it possible to find and classify thermal anomalies on video frames with an accuracy of 98%. The test results are presented, along with their validation based on thermal activity data obtained from satellite systems.
Korzhinsky M. A., Tkachenko S. I., Shmulovich K. I., Steinberg G. S. Native AI and Si formation // Nature. 1995. Vol. 375. № 6532. P. 544 doi:10.1038/375544a0.
Korzhinsky M. A., Tkachenko S. I., Shmulovich K. I., Taran Y. A., Steinberg G. S. Discovery of a pure rhenium mineral at Kudriavy volcano // Nature. 1994. Vol. 369. P. 51-52. doi: 10.1038/369051a0.
   Аннотация
KUDRIAVY volcano on Iturup island in the Kuril arc is an active calc-alkaline volcano. It has not erupted this century; its current volcanic activity is characterized by hot (up to 910oC) gas jets which have been stable for at least 30 years. The composition of the gaseous emissions is typical of high-temperature fumaroles, but we report here the discovery of unusual subsurface sublimates associated with one gas jet—a sulphide mineral containing rhenium as the only cation. To our knowledge, this is the first reported occurrence of a pure rhenium mineral. The concentration of rhen-ium in the fumarole gas is only 2–10 p.p.b., so the condensation of pure rhenium sulphide from this gas requires both enrichment of rhenium by eight orders of magnitude and remarkable selectivity. Rhenium is generally believed to exist in only trace amounts at the Earth's surface, but our findings demonstrate that it can be readily mobilized, dispersed and concentrated by degassing magmas.
Korzhinsky Mikhail A., Botcharnikov Roman E., Tkachenko Sergey I., Steinberg Genrikh S. Decade-long study of degassing at Kudriavy volcano, Iturup, Kurile Islands (1990–1999): Gas temperature and composition variations, and occurrence of 1999 phreatic eruption // Earth, Planets and Space. 2002. Vol. 54. № 3. P. 337-347. doi:10.1186/BF03353032.
   Аннотация
A high-temperature (up to 940°C) fumarolic activity at Kudriavy volcano had been studied during 1990–1999. The maximum gas temperatures of the fumaroles were measured in 1992 as 940°C, then gradually decreased with time and reached to 907°C in 1999. Gas composition of the high-temperature fumarole became enriched in H2O and depleted in other gas components, in particular in CO2. Hydrogen isotopic compositions of the high-temperature fumarolic gases were gradually depleted in deuterium. The gradual and continuous decrease in temperature and changes in gas composition observed during the last 10-year suggest that a magmatic melt have been degassing in a relatively steady-state manner from a single magma chamber. The detail investigations in 1998 and 1999 revealed short-term changes in gas composition characterized by sporadic increases in H2, CO2, and Stotal after intense precipitations. Small-scale eruptions occurred on October 7, 1999 at the summit. The ratios of major gas components (C/S, C/Cl, S/Cl, C/F, S/F, and Cl/F) significantly increased just prior to the eruption. The eruption at the Kudriavy volcano in 1999 was likely a phreatic eruption as a result of the intense precipitations after unusually long dry period. Meteoric water penetrated into the hot zone of volcano edifice and rapidly boiled causing the eruption.
Koulakov Ivan, Gordeev Evgeniy I., Dobretsov Nikolay L., Vernikovsky Valery A., Senyukov Sergey, Jakovlev Andrey, Jaxybulatov Kayrly Rapid changes in magma storage beneath the Klyuchevskoy group of volcanoes inferred from time-dependent seismic tomography // Journal of Volcanology and Geothermal Research. 2013. Vol. 263. P. 75 - 91. doi: 10.1016/j.jvolgeores.2012.10.014.
   Аннотация
We present the results of time-dependent local earthquake tomography for the Kluchevskoy group of volcanoes in Kamchatka, Russia. We consider the time period from 1999 to 2009, which covers several stages of activity of Kluchevskoy and Bezymianny volcanoes. The results are supported by synthetic tests that recover a common 3D model based on data corresponding to different time windows. Throughout the period, we observe a robust feature below 25 km depth with anomalously high Vp/Vs values (up to 2.2). We interpret this feature as a channel bringing deep mantle materials with high fluid and melt content to the bottom of the crust. This mantle channel directly or indirectly determines the activity of all volcanoes of the Kluchevskoy group. In the crust, we model complex structure that varies over time. During the pre-eruptive period, we detected two levels of potential magma storage: one in the middle crust at 10–12 km depth and one close to the surface just below Kluchevskoy volcano. In 2005, a year of powerful eruptions of Kluchevskoy and Besymiyanny volcanoes, we observe a general increase in Vp/Vs throughout the crust. In the relaxation period following the eruption, the Vp/Vs values are generally low, and no strong anomalous zones in the crust are observed. We propose that very rapid variations in Vp/Vs are most likely due to abrupt changes in the stress and deformation states, which cause fracturing and the active transport of fluids. These fluids drive more fracturing in a positive feedback system that ultimately leads to eruption. We envision the magma reservoirs beneath the Kluchevskoy group as sponge-structured volumes that may quickly change the content of the molten phases as fluids pulse rapidly through the system.