Integration of remote sensing techniques and models in nonlinear geomechanics tasks
Potapov V.P.1, Oparin V.N.2
1 Federal Research Center for Information and Computational Technologies (Kemerovo Branch), Kemerovo, Russian Federation
2 Mining Institute named after N.A. Chinakal, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russian Federation
Russian Mining Industry №S1 / 2023 р. 22-26
Abstract: The paper presents a methodological approach to creating state-of-the-art systems for integrated geomechanical monitoring of large-scale industrial mining facilities in Siberia using multimodal and digital factories of experimental and theoretical data of heterogeneous geoinformation. The monitoring tasks are solved using the principles of geomechanical thermodynamics that allow integral estimation of both geomechanical and thermal processes on the surface of mining operations. A hardware and software suite was developed for the information and analytical system to process satellite radar images, based on freely distributable software. Based on the calculations performed, a new algorithm was developed to assess landslide zones using multispectral and radar images. The developed complex is focused on the issues of geomechanical thermodynamics and makes it possible to solve the tasks of assessing the man-made impact of mining operations. Successful verification of the proposed approach has proved its high efficiency. The results of testing the information system in various operating modes are exemplified by solving important tasks at the Kuzbass and the Norilsk mining complex.
Keywords: information systems, information technologies, large-scale mining facilities, Siberia, metadata models, geodata bases, mining region, software testing, aerospace data
For citation: Potapov V.P., Oparin V.N. Integration of remote sensing techniques and models in nonlinear geomechanics tasks. Russian Mining Industry. 2023;(1 Suppl.):22–26. https://doi.org/10.30686/1609-9192-2023-S1-22-26
Article info
Received: 12.02.2023
Revised: 01.03.2023
Accepted: 02.03.2023
Information about the authors
Vadim P. Potapov – Dr. Sci. (Eng.), Chief Research Associate, Federal Research Center for Information and Computational Technologies (Kemerovo Branch), Kemerovo, Russian Federation; e-mail:This email address is being protected from spambots. You need JavaScript enabled to view it.
Victor N. Oparin – Corresponding Member of RAS, Dr. Sci. (Phys. and Math.), Mining Institute named after N.A. Chinakal, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russian Federation
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