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Название Determination results on potential production of open pit mines at cement raw material deposits in Russian regions by satellite remote sensing data
DOI 10.17580/em.2021.02.05
Автор Zenkov I. V., Morin A. S., Vokin V. N., Kiryushina E. V.
Информация об авторе

Siberian Federal University, Krasnoyarsk, Russia:

Zenkov I. V., Doctor of Engineering Sciences, Professor, zenkoviv@mail.ru
Morin A. S., Doctor of Engineering Sciences, Professor
Vokin V. N., Candidate of Engineering Sciences, Professor
Kiryushina E. V., Candidate of Engineering Sciences, Associate Professor

Реферат

The information obtained using the satellite technologies of remote sensing provides new massive knowledge about open pit mining operations at deposits of carbonate rocks for manufacture of cement in 26 regions of Russia. The number of mining and haulage machines operating in each individual open pit mine and within the whole cement industry sector is determined. The obtained information was used in the analytical estimation of each open pit mine capacity and the overall potential production in this sector. By the authors’ estimates, the annual technologically feasible volume of rock mass treated in 47 open pit mines of the cement industry is 190 Mt, including 135 Mt of useful minerals.

Ключевые слова Remote sensing, open pit mining, cement raw material deposit, open pit mine capacity, overall potential production, mining and haulage machines, remote monitoring
Библиографический список

1. Danilov R. Yu., Kremneva O. Yu., Ismailov V. Ya. et al. General methods and results of ground hyperspectral studies of seasonal changes in the reflective properties of crops and certain types of weeds. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa. 2020. Vol. 17, No. 1. pp. 113–127.
2. Efimov V. V., Yarovaya D. A., Komarovskaya O. I. Mesoscale polar cyclone from satellite data and results of numerical simulation. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa. 2020. Vol. 17, No. 1. pp. 223–233.
3. Zimin A. V., Atadzhanova O. A. estimation of the characteristics of mesoscale eddies in the basin of the Lofoten depression from satellite and ship observations. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa. 2020. Vol. 17, No. 3. pp. 202–210.
4. Lavrova O. Yu., Kostianoy A. G. Use of modern satellite data for monitoring wind surges. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa. 2020. Vol. 17, No. 2. pp. 227–242.
5. Terekhin E. A. Estimation of forest disturbance in the foreststeppe zone at the beginning of the XXI century using satellite data. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa. 2020. Vol. 17, No. 2. pp. 134–146.
6. Eric L. Bullock, Christoph Nolte, Ana L. Reboredo Segovia, Curtis E. Woodcock. Ongoing forest disturbance in Guatemala’s protected areas. Remote Sensing in Ecology and Conservation. 2020. Vol. 6, Iss. 2. рр. 141–152.
7. Oeser J., Heurich M., Senf C. et. al. Habitat metrics based on multi-temporal Landsat imagery for mapping large mammal habitat. Remote Sensing in Ecology and Conservation. 2020. Vol. 6, Iss. 1. рр. 52–69.
8. Lopatin J., Dolos K., Kattenborn T. et al. How canopy shadow affects invasive plant species classification in high spatial resolution remote sensing. Remote Sensing in Ecology and Conservation. 2019. Vol. 5, Iss. 4. рр. 302–317.
9. O’Brien T. G., Ahumada J., Akampurila E. et al. Camera trapping reveals trends in forest duiker populations in African National Parks. Remote Sensing in Ecology and Conservation. 2020. Vol. 6, Iss. 2. рр. 168–180.
10. LaRue M. A., Ainley D. G., Pennycook J. et al. Engaging ‘the crowd’ in remote sensing to learn about habitat affinity of the Weddell seal in Antarctica. Remote Sensing in Ecology and Conservation. 2020. Vol. 6, Iss. 1. рр. 70–78.
11. Elkind K., Sankey T. T., Munson S. M. et al. Invasive buffelgrass detection using high-resolution satellite and UAV imagery on Google Earth Engine. Remote Sensing in Ecology and Conservation. 2019. Vol. 5, Iss. 4. рр. 318–331.
12. Kattenborn T., Fassnacht F. E., Schmidtlein S. Differentiating plant functional types using reflectance: which traits make the difference? Remote Sensing in Ecology and Conservation. 2019. Vol. 5, Iss. 1. рр. 5–19.
13. Leitão P. J., Schwieder M., Pedroni F. et al. Mapping woody plant community turnover with space-borne hyperspectral data—a case study in the Cerrado. Remote Sensing in Ecology and Conservation. 2019. Vol. 5, Iss. 1. рр. 107–115.
14. Hsing P. Y., Bradley S., Kent V. T. et al. Economical crowdsourcing for camera trap image classification. Remote Sensing in Ecology and Conservation. 2018. Vol. 4, Iss. 4. рр. 361–374.
15. Zenkov I. V., Lukyanova A. A., Yuronen Yu. P. et al. Open pit mines at nonmetallic deposits in Russia from space. Mining and Disturbed Land Ecology. Krasnoyarsk : Sibirskiy federalnyi universitet, 2020. 652 p.
16. Available at: https://www.google.com/earth/ (accessed: 20.09.2021).
17. Available at: http://mining-enc.ru/ (accessed: 20.09.2021).

Полный текст статьи Determination results on potential production of open pit mines at cement raw material deposits in Russian regions by satellite remote sensing data
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