ABROAD
Original Paper
UDC 622.271(73):550.814 © I.V. Zenkov, Trinh Le Hung, E.V. Loginova, Yu.P. Yuronen, V.N. Vokin, E.V. Kiryushina, T.N. Sizova, K.V. Raevich, A.A. Latyntsev, 2024
ISSN 0041-5790 (Print) • ISSN 2412-8333 (Online) • Ugol’ – Russian Coal Journal, 2024, № 2, pp. 93-96
DOI: http://dx.doi.org/10.18796/0041-5790-2024-2-93-96
Title
SURFACE COAL PRODUCTION IN THE LIMPOPO PROVINCE IN THE TERRITORY OF THE REPUBLIC OF SOUTH AFRICA BASED ON SATELLITE IMAGING DATA
Authors
Zenkov I.V.1, Trinh Le Hung2, Loginova E.V.3, Yuronen Yu.P.3, Vokin V.N.4, Kiryushina E.V.4, Sizova T.N.4, Raevich K.V.4, Latyntsev A.A.4
1Siberian Research Institute of Mining and Surveying, Krasnoyarsk, 660064, Russian Federation
2Le Quy Don Technical University (LQDTU), Hanoi, 11355, Vietnam
3Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, 660037, Russian Federation
4Siberian Federal University, Krasnoyarsk, 660041, Russian Federation
Authors Information
Zenkov I.V., Doctor of Engineering Sciences, Professor, Deputy Director for Scientific Work, e-mail: zenkoviv@mail.ru
Trinh Le Hung, PhD (Engineering), Associate Professor
Loginova E.V., PhD (Economic), Associate Professor
Yuronen Yu.P., PhD (Engineering), Associate Professor
Vokin V.N., PhD (Engineering), Professor
Kiryushina E.V.,PhD (Engineering), Associate Professor
Sizova T.N.,Senior lecturer
Raevich K.V., PhD (Engineering), Associate Professor
Latyntsev A.A., PhD (Engineering), Associate Professor
Abstract
The geography of the coal mining pit and the thermal power plants based on coal combustion has been determined in the Limpopo Province in the Republic of South Africa. The paper presents the results of studying the current state of surface mining of a large-scale deposit of high-grade coals, using remote sensing data from space. The production potential of the operating open-pit coal mine has been identified in the course of remote monitoring and analytical calculations.
Keywords
Earth remote sensing from space, Republic of South Africa, Limpopo Province, Fuel and energy complex, Coal open-pit mines, Thermal electric power plants, Coal-fired electric power generation, Coal mining and consumption volumes, Distribution of production operations.
References
1. 1. Terekhin E.A. Influence of forest cover of the fallow lands in the forest-steppe on the spectral-reflectance characteristics based on Sentinel-2 data. Sovremennye problemy distancionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, (4), pp. 223-235. (In Russ.).
2. Raevsky B.V., Tarasenko V.V. & Petrov N.V. Assessment of current state of plant communities in the Kostamuksha Natural Park based on Landsat satellite images. Sovremennye problemy distancionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, (3), pp. 47-61. (In Russ.).
3. Ozaryan Yu.A., Bubnova M.B. & Usikov V.I. Methodology of remote monitoring of natural and technological systems (in conditions of mining areas in the south of the Russian Far East). Gornyj zhurnal, 2020, (2), pp. 84-87. (In Russ.).
4. 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, Vol. 26, (1), pp. 24-29.
5. Zenkov I.V., Morin A.S., Vokin V.N. & Kiryushina E.V. Remote sensing of mining and haul-age equipment arrangement in Russia: A case-study of the coal and iron ore industry. Eurasian mining, 2020, (2), pp. 46–49.
6. Cie?lik K. & Milczarek W. Application of Machine Learning in Forecasting the Impact of Mining Deformation: A Case Study of Underground Copper Mines in Poland. Remote Sensing, 2022;14(19):4755. https://doi.org/10.3390/rs14194755.
7. Jiao R., Wang S., Yang H., Guo X., Han J., Pei X. & Yan C. Comprehensive Remote Sensing Technology for Monitoring Landslide Hazards and Disaster Chain in the Xishan Mining Area of Beijing. Remote Sensing, 2022;14(19):4695. https://doi.org/10.3390/rs14194695.
8. Yang W., Mu Y., Zhang W., Wang W., Liu J., Peng J., Liu X. & He T. Assessment of Ecological Cumulative Effect due to Mining Disturbance Using Google Earth Engine. Remote Sensing, 2022;14(17):4381. https://doi.org/10.3390/rs14174381.
9. Tian H., Liu S., Zhu W., Zhang J., Zheng Y., Shi J. & Bi R. Deciphering the Drivers of Net Primary Productivity of Vegetation in Mining Areas. Remote Sensing, 2022;14(17):4177. https://doi.org/10.3390/rs14174177.
10. Google Earth. [Electronic resource]. Available at: https://www.google.com.earth/ (accessed 15.01.2024).
Acknowledgements
The study was performed within the framework of international cooperation in expanding the use of remote sensing technologies.
For citation
Zenkov I.V., Trinh Le Hung, Loginova E.V., Yuronen Yu.P., Vokin V.N., Kiryushina E.V., Sizova T.N., Raevich K.V. & Latyntsev A.A. Surface coal production in the Limpopo Province in the territory of the Republic of South Africa based on satellite imaging data. Ugol’, 2024, (2), pp. 93-96. (In Russ.). DOI: 10.18796/0041-5790-2024-2-93-96.
Paper info
Received Octoberber 31, 2023
Reviewed January 15, 2024
Accepted January 26, 2024
