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Results of Remote Monitoring of the Technological Potential and Ecology of Open-pit Mining at Mineral Deposits for the Production of Crushed Stone

https://doi.org/10.18412/1816-0395-2024-1-40-45

Abstract

Based on the results of remote monitoring, the state of mining operations in quarries for the extraction of mineral raw materials consumed by crushed stone plants in Russia was investigated. The indicators of integrated mechanization of crushed stone quarries based on the presence of operating mining and transport vehicles have been identified. The production capacity of each quarry in terms of rock mass and the total production potential of the crushed stone plants in Russia, estimated at 285 million tons per year, have been determined. The environmental indicators of disturbed lands during the development of mineral deposits for use in the crushed stone plants are presented.

About the Authors

I.V. Zenkov
Siberian Research Institute of Mining and Surveying
Russian Federation

Dr. Sci. (Eng.), Deputy Director for Research



E.A. Kustikova
Siberian Research Institute of Mining and Surveying
Russian Federation

Engineer-elocogist



Chin Le Hung
Le Quy Don Technical University
Viet Nam

Cand. Sci. (Eng.), Associate Professor



M.L. Dmitrieva
Saint Petersburg Mining University
Russian Federation

Cand. Sci. (Economics), Associate Professor



Yu.P. Yuronen
Reshetnev Siberian State University of Science and Technology
Russian Federation

Cand. Sci. (Eng.), Associate Professor



E.V. Cherepanov
Siberian Federal University
Russian Federation

Cand. Sci. (Eng.), Associate Professor



E.I. Gerasimova
Siberian Federal University
Russian Federation

Senior Lecturer



P.M. Kondrashov
Siberian Federal University
Russian Federation

Cand. Sci. (Eng.), Professor



Zh.V. Mironova
Siberian Federal University
Russian Federation

Cand. Sci. (Eng.), Associate Professor



S.N. Skornyakova
Siberian Federal University
Russian Federation

Senior Lecturer



References

1. Пономаренко М.Р., Кутепов Ю.И., Шабаров А.Н. Информационно-аналитическое обеспечение мониторинга состояния объектов открытых горных работ на базе технологий веб-картографии. Горный информационно-аналитический бюллетень. 2022. № 8. С. 56—70.

2. Константинова А.М., Балашов И.В., Кашницкий А.В. и др. Унифицированная технология дистанционного мониторинга природных и антропогенных объектов. Современные проблемы дистанционного зондирования Земли из космоса. 2021. Т. № 4. С. 41—52.

3. Лупян Е.А., Константинова А.М., Балашов И.В. и др. Разработка системы анализа состояния окружающей среды в зонах расположения крупных промышленных объектов, хвостохранилищ и отвалов. Современные проблемы дистанционного зондирования Земли из космоса. 2020. Т. 17. № 7. С. 243—261.

4. Пашкевич М.А., Петрова Т.А., Рудзиш Э. Оценка потенциальной возможности использования лигнин-шламов для лесохозяйственной рекультивации нарушенных земель. Записки Горного института. 2019. 235. P. 106. https://doi.org/10.31897/pmi.2019.1.106.

5. Zenkov I.V., Le Hung T., Vokin V.N. et al. Space-based Applications of Remote Sensing in Studying Opencast Mining and Ecology at Deposits of Non-ferrous Metal Ore. Ecology and Industry of Russia. 2022. V. 26. I. 1. Р 24—29.

6. Yue Han, Yinghai Ke, Lijuan Zhu et al. Tracking vegetation degradation and recovery in multiple mining areas in Beijing, China, based on time-series Landsat imagery. GIScience & Remote Sensing. 2021. V. 58. I. 8. P. 1477—1496. DOI: 10.1080/15481603.2021.1996319.

7. Bangira T., Alfieri S.M., Menenti M., van Niekerk A. Comparing Thresholding with Machine Learning Classifiers for Mapping Complex Water. Remote Sens. 2019. 11. 1351. doi.org/10.3390/rs11111351.

8. Felipe L. Lobo, Maycira P.F. Costa, Evlyn M.L.M. Novo. Time-series analysis of Landsat-MSS/TM/OLI images over Amazonian waters impacted by gold mining activities. Remote Sensing of Environment. 2015, V. 157, Р. 170-184.

9. Sekandari M., Masoumi I., Beiranvand Pour A. et al. Application of Landsat-8, Sentinel-2, ASTER and WorldView-3 Spectral Imagery for Exploration of Carbonate-Hosted Pb-Zn Deposits in the Central Iranian Terrane (CIT). Remote Sens. 2020. 12(8):1239. doi.org/10.3390/rs12081239.

10. Bolouki S.M., Ramazi H.R., Maghsoudi A. et al. А Remote Sensing-Based Application of Bayesian Networks for Epithermal Gold Potential Mapping in Ahar-Arasbaran Area, NW Iran. Remote Sens. 2020. 12(1):105. doi.org/10.3390/rs12010105.

11. Yao F., Xu X., Yang J., Geng X. A Remote-Sensing-Based Alteration Zonation Model of the Duolong Porphyry Copper Ore District, Tibet. Remote Sens. 2021. 13(24):5073. doi.org/10.3390/rs13245073.

12. https://www.google.com.earth.


Review

For citations:


Zenkov I., Kustikova E., Le Hung Ch., Dmitrieva M., Yuronen Yu., Cherepanov E., Gerasimova E., Kondrashov P., Mironova Zh., Skornyakova S. Results of Remote Monitoring of the Technological Potential and Ecology of Open-pit Mining at Mineral Deposits for the Production of Crushed Stone. Ecology and Industry of Russia. 2024;28(1):40-45. (In Russ.) https://doi.org/10.18412/1816-0395-2024-1-40-45

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ISSN 1816-0395 (Print)
ISSN 2413-6042 (Online)