Geological interpretation of remote sensing data using the case of the Kolmozerskoye field in the Murmansk region

DOI: https://doi.org/10.30686/1609-9192-2024-3-122-125

Читать на русскоя языкеA.A. Kamaev1, 2, A.I. Manevich1, 2, V.V. Antoshin3
1 Geophysical Center, Russian Academy of Sciences, Moscow, Russian Federation
2 National University of Science and Technology MISIS, Moscow, Russian Federation
3 NGK Gorny LLC, Moscow, Russian Federation

Russian Mining Industry №3 / 2024 стр. 122-125

Abstract: This article discusses the need for the development of Russia's mineral and raw material base to support the country's high-tech economy. Special attention is given to prospecting and mining of strategically important types of raw materials, such as titanium, tungsten, lithium, and others. The importance of securing resources from domestic sources, minimizing dependence on imports, is emphasized. The article describes remote survey methods, specifically the use of Earth remote sensing data, i.e. the satellite images, for prospecting and assessment of potential deposits. An analysis of satellite data of the Murmansk Oblast is conducted to identify the potential mineralization nodes. The methods used include interpretation of images using geological indexes. With their help, zones of geological interest can be identified, which can later be used in a full range of geological exploration activities.

Keywords: mineral and raw material base, strategic types of raw materials, geological exploration, remote sensing of Earth, satellite imagery, Murmansk region, mineralization nodes

For citation: Kamaev A.A., Manevich A.I., Antoshin V.V. Geological interpretation of remote sensing data using the case of the Kolmozerskoye field in the Murmansk region. Russian Mining Industry. 2024;(3):122–125. (In Russ.) https://doi.org/10.30686/1609-9192-2024-3-122-125


Article info

Received: 29.03.2024

Revised: 06.05.2024

Accepted: 08.05.2024


Information about the authors

Artyom A. Kamaev – Engineer, Laboratory of GEODYNAMICS, Geophysical Center, Russian Academy of Sciences, Postgraduate Student of the Department of the Geology and Surveying, National University of Science and Technology MISIS, Moscow, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Alexandr I. Manevich – Research Scientist, Laboratory of Geodynamics, Geophysical Center, Russian Academy of Sciences, Lecturer of the Department of the Geology and Surveying, National University of Science and Technology MISIS, Moscow, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Vladislav V. Antoshin – Director of Industrial Safety, Health and Environment Safety Department, NGK Gorny LLC, Moscow, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.


References

1. Хатьков В.Ю., Боярко Г.Ю. Ранжирование видов минерального сырья России по импортозависимости. Интерэкспо Гео-Сибирь. 2023;2(4):108–114. https://doi.org/10.33764/2618-981X-2023-2-4-108-114 Khatkov V.Yu., Boyarko G.Yu. Ranking of types of mineral raw materials in Russia by import dependence. Interekspo GeoSibir’. 2023;2(4):108–114. (In Russ.) https://doi.org/10.33764/2618-981X-2023-2-4-108-114

2. Мингалеева Р.Д. Запасы и добыча редкоземельных металлов и элементов – ключевой фактор развития возобновляемой энергетики на современном этапе трансформации мировой экономики. Вестник университета. 2023;(5):37–45. https://doi.org/10.26425/1816-4277-2023-5-37-45 Mingaleeva R.D. Reserves and extraction of rare earth metals and elements as a key factor in the renewable energy sector development at the world economy transformation current stage. Vestnik Universiteta. 2023;(5):37–45. (In Russ.) https://doi.org/10.26425/1816-4277-2023-5-37-45

3. Кондратьев В.Б. Китай в глобальной горной промышленности. Горная промышленность. 2023;(3):78–87. https://doi.org/10.30686/1609-9192-2023-3-78-87 Kondratiev V.B. China in Global Mining Industry. Russian Mining Industry. 2023;(3):78–87. (In Russ.) https://doi.org/10.30686/1609-9192-2023-3-78-87

4. Кондратьев В.Б. Роль критически важных сырьевых материалов в экономике США. Горная промышленность. 2022;(5):121–130. https://doi.org/10.30686/1609-9192-2022-5-121-130 Kondratiev V.B. The Role of Critical Raw Materials in US Economy. Russian Mining Industry. 2022;(5):121–130. (In Russ.) https://doi.org/10.30686/1609-9192-2022-5-121-130

5. Drury S.A. Image interpretation in geology. London: Allen & Unwin; 1987. 243 p.

6. Sabins F.F. Remote Sensing: Principles and interpretation. 2nd ed. New York: Freeman; 1986. 494 p.

7. Gorelick N., Hancher M., Dixon M., Ilyushchenko S., Thau D., Moore R. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment. 2017;202:18–27. https://doi.org/10.1016/j.rse.2017.06.031

8. Sabins F.F. Remote sensing for mineral exploration. Ore Geology Reviews. 1999;14(3-4):157–183. https://doi.org/10.1016/S0169-1368(99)00007-4

9. Gao Y., Bagas L., Li K., Jin M., Liu Y., Teng J. Newly discovered Triassic lithium deposits in the Dahongliutan area, NorthWest China: A case study for the detection of Lithium-Bearing pegmatite deposits in rugged terrains using Remote-Sensing Data and images. Frontiers in Earth Science (Lausanne). 2020;8:591966. https://doi.org/10.3389/feart.2020.591966

10. Cardoso-Fernandes J., Silva J., Perrotta M.M., Lima A., Teodoro A.C., Ribeiro M.A. et al. Interpretation of the reflectance spectra of Lithium (LI) minerals and pegmatites: A case study for mineralogical and lithological identification in the Fregeneda-Almendra area. Remote Sensing. 2021;13(18):3688. https://doi.org/10.3390/rs13183688