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About the Authors
Tatiana P. Varshanina
13 Gagarina St., 385000, Maykop, Russia;
E-mail: vtp01@mail.ru
Rashid D. Khunagov
13 Gagarina St., 385000, Maykop, Russia;
E-mail: khunagov-rd@mail.ru
Viktor N. Korobkov
13 Gagarina St., 385000, Maykop, Russia;
E-mail: gic-info@yandex.ru
Abstract
The paper discusses informative possibilities and prospects of application of digital nature-like methodology for computational visualization of natural processes of natural system formation based on the proposed order parameter—intensity of integral geophysical field created by host structure-forming outer space. Since the designated order parameter defines the structure and properties of natural systems and processes, the gradient of the parameter defining the structure of the natural object is a measure of its order parameter and, therefore, can serve as a predictor of forecasting the change in its properties and structure. The declared approach is tested using an example of forecasting the process of flood formation and processes of visualization of tectonic stress fields. The authors have developed a method of point prediction of the onset time and flood level based on a three-level neural network model and a method of vector space-time visualization of a hierarchy of tectonic stress fields on the territory of an unlimited area. The research shows that computational operations with the parameter of the regional temperature gradient along with intelligent forecasting methods illustrate the prospects of point medium-, long-term forecasting of hydrometeorological processes provided with long rows of instrumental observation data.
Computational visualization of general, background and local fields of tectonic stresses in the territories of unlimited area serves as a source of parametric data for geoinformation-mathematical modeling of tectonic stress field restructuring in processes of tectonosphere self-organization, calculation of position of geodynamic instability loci—epicenters of possible earthquakes, visualization of tectonic currents in the Earth’s crust. Monitoring geophysical data at geodynamic instability loci opens up prospects for point prediction of earthquakes. Calculation of order parameters of natural objects and processes opens up prospects of their computational modeling, derivation of numerical laws of their conjugate development and a scale series of interaction, as well as prediction of the state of geo objects and geo processes at a given geo space point in conditions of increasing global natural variability.
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References
- Andreev V.K., Baranov G.I., Grekov I.I. et al. Tectonic map of the Northwestern Caucasus.: Yessentuki. 1999. 104 p. (in Russian).
- Filosofov V.P. Brief guide to the morphometric method of searching for tectonic structures. Saratov: Publishing House of Saratov University, 1960. 69 p. (in Russian).
- Filosofov V.P. Fundamentals of the morphometric method of searching for tectonic structures. Saratov: Publishing House of Saratov University, 1975. 232 p. (in Russian).
- Godzikovskaya A.A. Catalog of earthquakes in the Caucasus, 2010. Web resource: http://www.wdcb.ru/sep/seismology/method/Caucasus/index.ru.html (accessed 19.06.2013) (in Russian).
- Goncharov M.A., Talitsky V.G., Frolova N.S. Introduction to tectonophysics. Moscow: KDU, 2005. 496 p. (in Russian).
- Lukyanov A.V. Plastic deformations and tectonic flow in the lithosphere. Moscow: Nauka, 1991. 144 p. (in Russian).
- Malinetsky G.G. Mathematical foundations of synergetics: chaos, structures, computational experiment. Moscow: Publishing house LKI, 2007. (in Russian).
- Nazarov A.V., Loskutov A.I. Neural network algorithms for forecasting and optimizing systems. St. Petersburg: Science and Technology, 2003. 384 p. (in Russian).
- Olemskoy A.I. Synergetics of Complex Systems: Phenomenology and Statistical Theory. Moscow: URSS, 2009. 378 p. (in Russian).
- Osovsky S. Neural networks for information processing. Moscow: Finance and statistics, 2002. 344 p. (in Russian).
- Pribylova N.E., Besstrashnov V.M., Godzikovskaya A.A. Does the source of the earthquake on November 23, 1899 belong to the Kamchatka seismically active zone? Volcanology and seismology, 2006. No. 2. P. 46–54 (in Russian).
- Talitsky V.G. Modeling of tectonic deformations taking into account heterogeneities of the geological environment. In the “Introduction to tectonophysics”. M.A. Goncharov et al. Moscow: KDU, 2005. P. 204–247 (in Russian).
- Varshanina T.P., Korobkov V.N. Spatial-Temporal Geodynamic Model of Adygea. The Republic of Adygea Environment, 2020. P. 85–112. DOI: 10.1007/698_2020_500.
- Varshanina T.P., Plisenko O.A., Solodukhin A.A., Korobkov V.N. Structural-like geodynamic model of the Krasnodar Territory and the Republic of Adygea. Moscow–Maykop: “Kamerton” Publishing House, 2011. 128 p. (in Russian).
- Varshanina T.P. Development of a well-structured geospace model based on the structural mask method of energy geofields. Bulletin of the Adyghe State University. Series 4: Natural-mathematical and technical sciences, 2012. No. 4 (110). P. 176–179 (in Russian).
- Varshanina T.P., Plisenko O.A., Korobkov V.N. Methodology and scientific and practical significance of visualization of integral geophysical fields. Electronic journal MEPhI “Scientific visualization”, 2017. V. 9. No. 4. P. 108–117 (in Russian). DOI: 10.26583/sv.9.4.11.
For citation: Varshanina T.P., Khunagov R.D., Korobkov V.N. Information content of geoinformation computational visualization of natural object formation processes. InterCarto. InterGIS. GI support of sustainable development of territories: Proceedings of the International conference. Moscow: MSU, Faculty of Geography, 2022. V. 28. Part 1. P. 508–522. DOI: 10.35595/2414-9179-2022-1-28-508-522 (in Russian)