Geoinformation monitoring for solving environmental problems of mining territories of the Middle Ural

DOI: https://doi.org/10.30686/1609-9192-2022-1S-127-133

S.V. Kornilkov¹, L.S. Rybnikova¹, P.A. Rybnikov^{1, 2}, A.Yu. Smirnov^{1, 2} ¹ Institute of Mining of Ural Branch of RAS, Ekaterinburg, Russian Federation ² Ural State Mining University, Ekaterinburg, Russian Federation Russian Mining Industry №1S / 2022 р. 127-133

Abstract: Geographic information monitoring is shown as the leading method of process control in old industrial territories. The main stages of geoinformation monitoring are outlined. The role of geographic information systems in the study of pollution components, systematization and accumulation of spatially distributed data, analysis and development of predictive solutions is considered. The solution of the problem of the conceptual organization of the geoinformation system of mining territories has been substantiated. The structure of software products and geographic information systems selection criteria are considered. The QGIS software product was chosen as the desktop geographic information systems. The functionality of JavaScript-libraries Leaflet and Highcharts, the possibility of their use as a web-based geographic information systems are described. The structure of the base layers of the geographic information systems, created for the organization of geoinformation monitoring of the old industrial territory of the Levikhinsky mine, is described. An algorithm for organizing spatially distributed data of the monitoring object, a fundamental algorithm for data processing are proposed. Considerable attention is paid to the typification and subsequent differentiation of the types of initial information, the storage of geographic information systems data in exchange formats. The author's algorithm of interaction between desktop and web-based geographic information systems is described. The provisions and technical solutions set out in the article allow using geographic information systems for operational monitoring, forecasting and comprehensive assessment, and management decisions.

Keywords: geoinformation monitoring, Geographic Information Systems, GIS, Environmental monitoring, Levikha copper mine, Geoinformatics, QGIS, Leaflet, Highcharts

Acknowledgments: The paper was prepared within the framework of the State Contract with Institute of Mining of Ural Branch of RAS No.0328-2019-0005.

For citation: Kornilkov S.V., Rybnikova L.S., Rybnikov P.A., Smirnov A.Yu. Geoinformation monitoring for solving environmental problems of mining territories of the Middle Ural. Gornaya promyshlennost = Russian Mining Industry. 2022;(1 Suppl.):127–133. DOI: https://doi.org/10.30686/1609-9192-2022-1S-127-133

Article info

Received: 08.10.2021

Revised: 27.10.2021

Accepted: 29.10.2021

Information about the authors

Sergey V. Kornilkov – Dr. Sci. (Eng.), Professor, Member of the Academy of Mining Sciences, Chief Researcher, Institute of Mining of Ural Branch of RAS, Ekaterinburg, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Ludmila S. Rybnikova – Doctor of Science in Geology and Mineralogy, Main Scientist Researcher Laboratory of Ecology of Mining Production, Institute of Mining of Ural Branch of RAS, Ekaterinburg, Russian Federation

Petr A. Rybnikov – Cand Sci. (Geological and Mineralogical), Head of the Laboratory of Geoinformation and Digital Technologies in Subsoil Use, Institute of Mining of Ural Branch of RAS; Associate Professor, Department of Environmental Engineering, Ural State Mining University, Ekaterinburg, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Alexander Yu. Smirnov – Junior Researcher, Laboratory of Geoinformation and Digital Technologies in Subsoil Use, Institute of Mining of Ural Branch of RAS; Lecturer, Department of Geodesy and Cadastres, Ural State Mining University, Ekaterinburg, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

References

1. Kornilkov S.V., Antoninova N.Iu., Panzhin A.A., Shubina L.A., Isakov S.V. Specifying the approaches to geoinformation monitoring to assess the development dynamics of mining enterprises as natural-technological systems. Izvestiya vysshikh uchebnykh zavedenii. Gornyi zhurnal = News of the Higher Institutions. Mining Journal. 2020;(8):41–51. https://doi.org/10.21440/0536-10282020-8-41-51

2. Smirnov A.Y., Rybnikov P.A. Experience of geostatistic methods application to assess air pollution around an industrial enterprise (the Middle Urals). MIAB. Mining Inf. Anal. Bull. 2019;(S37):596–605. (In Russ.) https://doi.org/10.25018/0236-1493-2019-11-37-596-605

3. Smirnov A.Yu., Rybnikov P.A. Detection of geochemical anomalies and determination of air pollution sources using an industrial enterprise (Middle Urals) as an example. In: 12th Sergeev’s Readings: geo-ecological aspects of implementing the 'Ecology' national project. Dialogue of Generations: proceedings of the International Research Conference, Moscow, March 24, 2020. Moscow: RUDN University; 2020, pp. 78–81. (In Russ.)

4. Cannata M., Neumann J., Rossetto, R. Open source GIS platform for water resource modelling: FREEWAT approach in the Lugano Lake. Spatial Information Research. 2018;26(3):241–251. https://doi.org/10.1007/s41324-017-0140-4

5. Li Z. Watershed modeling using arc hydro based on DEMs: a case study in Jackpine watershed. Environmental Systems Research. 2014;3:11. https://doi.org/10.1186/2193-2697-3-11

6. Riabova S.A. Temporary variations of magnetotelluric function (magnetic tipper) and their possible relationship with variations of groundwater level. Problemy nedropolzovaniya. 2020;(2):174–180. (In Russ.) https://doi.org/10.25635/2313-1586.2020.02.174

7. Hugentobler M. Quantum GIS. In: Shekhar S., Xiong H., Zhou X. (eds) Encyclopedia of GIS. Springer; 2017, pp. 1695–1716. https://doi.org/10.1007/978-3-319-17885-1_1064

8. Crickard P. Leaflet.js Essentials. UK, Packt Publishing Ltd.; 2014. 180 p. Available at: https://www.programmer-books.com/wp-content/uploads/2019/05/Leaflet.js-Essentials.pdf

9. Trilles S., Schade S., Belmonte Ó., Huerta J. Real-time anomaly detection from environmental data streams. In: Bacao F., Santos M., Painho M. (eds) AGILE 2015. Lecture Notes in Geoinformation and Cartography. Springer; 2015. pp. 125–144. https://doi.org/10.1007/978-3-319-16787-9_8

10. Biktashev T.U., Fedorov N.I., Baisheva E.Z. About the Project of the Web GIS “Electronic Atlas of Bryophytes of the Republic of Bashkortostan”. In: Bychkov I., Voronin V. (eds) Information Technologies in the Research of Biodiversity. Springer; 2019. pp. 80–85. https://doi.org/10.1007/978-3-030-11720-7_12

11. Mishra S. Practical highcharts with angular. Apress, Berkeley, CA; 2020. 302 p. https://doi.org/10.1007/978-1-4842-5744-9

12. Lumbroso D., Collell M.R., Petkovsek G., Davison M., Liu Y., Goff C., Wetton M. DAMSAT: An eye in the sky for monitoring tailings dams. Mine Water Environ. 2021;40(1):113–127. https://doi.org/10.1007/s10230-020-00727-1