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ENVIRONMENTAL PROTECTION
Название Analysis of mineral indices from remote sensing: a case-study of the Tokrau river
DOI 10.17580/em.2024.01.17
Автор Orynbassarova E. O., Adebiyet B., Iliuf F. A., Sydyk N. K.
Информация об авторе

Satbayev University, Almaty, Kazahstan

Orynbassarova E. O., Head of the Department, Associate Professor, e.orynbassarova@satbayev.university
Adebiyet B., PhD Student
Iliuf F. A., Student, Master of Engineering Sciences

 

Institute of Ionosphere LLP, Almaty, Kazahstan
Sydyk N. K., Head of Laboratory, Candidate for a Doctor’s Degree

Реферат

The study focuses on the use of the Earth Remote Sensing (ERS) data to calculate mineral indices using the example of the Tokrau River. In the modern era, as issues of climate change and human impact on the environment become increasingly prominent, monitoring natural resources has become imperative. In this regard, remote sensing technologies provide valuable data for the study and control of Earth’s resources. The aim of this research is to investigate changes in the mineral composition in the Tokrau River valley using information obtained during Landsat and Sentinel-2A missions from 1998 to 2021 to assess human impact on the ecosystem and to find potential mineral deposits. This work is important both scientifically and practically as it demonstrates that spectral mapping can effectively detect mineral changes. This finding is significant for geological research and environmental monitoring. The research approach included the examination of satellite data, calculation of mineral indices, and comparison of the results obtained in different time periods. The collected data allowed for conclusions to be drawn regarding fluctuations in mineral transformations in the Tokrau River valley. The study complements existing knowledge about the use of remote sensing in geological research and environmental monitoring. It also contributes to international experience in this field. The practical significance of the research lies in utilizing the collected data to develop methods for the protection and responsible use of natural resources in the Tokrau River region and other comparable regions.
The research is funded by the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. BR21882179).

Ключевые слова Earth remote sensing (ERS), mineral indices, Tokrau River, spectral analysis, Landsat, Sentinel-2A
Библиографический список

1. Baugh W. M., Kruse F. A., Atkinson Jr. W. W. Quantitative Geochemical Mapping of Ammonium Minerals in the Southern Cedar Mountains, Nevada, Using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Remote Sensing of Environment. 1998. Vol. 65, No. 3. pp. 292–308.
2. Abrams M. J., Brown D. Silver Bell, Arizona, porphyry copper test site. The Joint NASA — Geosat test case study, Section 4. American Association of Petroleum Geologists. 1985. 73 p.
3. Sabins F. F. Remote sensing for mineral exploration. Ore Geology Reviews. 1999. Vol. 14, Iss. 3–4. pp. 157–183.
4. Spatz D. M., Wilson R. T. Exploration remote sensing for porphyry copper deposits, western America Cordillera. Proceedings of the Tenth Thematic Conference on Geologic Remote Sensing. Environmental Research Institute of Michigan, 1994. pp. 1227–1240.
5. Sabins F. F. Remote sensing — Principles and interpretation, 3rd ed. New York : W. H. Freeman and Co., 1997. 494 p.
6. Watson K., Kruse F. A., Hummer-Miller S. Thermal infrared exploration in the Carlin trend, northern Nevada. Geophysics. 1990. Vol. 55. pp. 70–79.
7. Bennett S. A., Atkinson W. W., Kruse F. A. Use of thematic mapper imagery to identify mineralization in the Santa Teresa District, Sonora, Mexico. International Geology Review. 1993. Vol. 35, Iss. 11. pp. 1009–1029.
8. Zhang X., Pazner M., Duke N. Lithologic and mineral information extraction for gold exploration using ASTER data in the south Chocolate Mountains (California). ISPRS Journal of Photogrammetry and Remote Sensing. 2007. Vol. 62, Iss. 4. pp. 271–282.
9. Baibatsha A. B., Mamanov E. Zh. Geology and geodynamics of Karsakpay–Ulytau geostuture zone and its prospects for minerals. News of the Academy of Sciences of the Republic of Kazakhstan. Series of Geology and Technical Sciences. 2017. Vol. 1, No. 421. pp. 46–62.
10. Baibatsha A. B., Omarova G., Dyussembayeva K. Sh., Kassenova A. T. Kokkiya — A promising for Kazakhstan gold-metasomatic type of deposit. 16th International Multidisciplinary Scientific Geoconference — SGEM 2016. 2016. Vol. 1. 2016. pp. 289–296.
11. Baibatsha A. B., Bekbotaeva A. A., Bekbotayev A. T. Ore minerals of Carboniferous copper sediment-hosted Zhezkazgan deposit (Central Kazakhstan). Proceedings of the 15th International Multidisciplinary Scientific GeoConference — SGEM 2015. 2015. pp. 329–337.
12. Stasiv I. V. On the origin of lake Balkhash and Balkhash — Alakol depression. 2020. Sci-Article.ru. No. 78. pp. 11–20.
13. Egizkoitas. Kazakhstan. National Encyclopedia. Almaty : Kazak entsiklopediyasy, 2005. Vol. II.
14. The Great Soviet Encyclopedia. Prohorov A. M. 3rd edition. Moscow : Sovetskaya entsiklopedia, Vol. 30. 1978. 631 p.
15. Mars J. C., Rowan L. C. Spectral assessment of new ASTER SWIR surface reflectance data products for spectroscopic mapping of rocks and minerals. Remote Sensing of Environment. 2010. Vol. 114, Iss. 9. pp. 2011–2025.
16. Pour B. A., Hashim M. The application of ASTER remote sensing data to porphyry copper and epithermal gold deposits. Ore Geology Reviews. 2012. Vol. 44, pp. 1–9.
17. Noori L., Pour B. A., Askari G. et al. Comparison of different algorithms to map hydrothermal alteration zones using aster remote sensing data for polymetallic vein-type ore exploration: Toroud–Chahshirin Magmatic Belt (TCMB), North Iran. Remote Sensing. 2019. Vol. 11, Iss. 5. ID 495.
18. Ninomiya, Y., Fu B. Thermal infrared multispectral remote sensing of lithology and mineralogy based on spectral properties of materials. Ore Geology Reviews. 2019. Vol. 108. pp. 54–72.
19. Pour A. B., Park Y., Park T. S. et al. Regional geology mapping using satellitebased remote sensing approach in Northern Victoria Land, Antarctica. Polar Science. 2018. Vol. 16. pp. 23–46.
20. Bolouki, S. M., Ramazi H. R., Maghsoudi A., Pour A. B., Sohrabi G. A Remote sensing-based application of Bayesian networks for epithermal gold potential mapping in Ahar-Arasbaran Area, NW Iran. Remote Sensing. 2020. Vol. 12, Iss. 1. ID 105.
21. Sekandari M., Masoumi I., Pour A. B. 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 Sensing. 2020. Vol. 12, Iss. 8. ID 1239.

22. Mars J. C., Rowan L. C. Regional mapping of phyllic-and argillic-altered rocks in the Zagros magmatic arc, Iran, using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data and logical operator algorithms. Geosphere. 2006. Vol. 2(3). pp. 161–186.
23. Available at: https://www.usgs.gov/landsat-missions/landsat-satellite-missions (Accessed: 04.04.2024).
24. Duuring P., Hagemann S. G., Novikova Y., Cudahy T., Laukamp C. Targeting iron ore in banded iron formations using ASTER data: Weld Range Greenstone Belt, Yilgarn Craton, Western Australia. Economic Geology. 2012. Vol. 107. pp. 585–597.
25. Ducart D. F., Silva A. M.; Toledo B., Assis L. Mapping iron oxides with Landsat-8/OLI and EO-1/Hyperion imagery from the Serra Norte iron deposits in the Carajás Mineral Province, Brazil. Brazilian Journal of Geology. 2016. Vol. 46. pp. 331–349.
26. Available at: https://sentinel.esa.int/web/sentinel/missions/sentinel-2 (Accessed: 04.04.2024).
27. Dogan H. M. Mineral composite assessment of Kelkit River Basin in Turkey by means of remote sensing. Journal of Earth System Science. 2009. Vol. 118. pp. 701–710.
28. Bergaya F., Theng B. K. G., Lagaly G. Developments in Clay Science Series. Handbook of Clay Science. Amsterdam : Elsevier, 2006. 1224 p.
29. ArcGIS. Channel Indexes. Available at: https://pro.arcgis.com/ru/pro-app/latest/arcpy/spatial-analyst/bai.html (Accessed: 04.04.2024).
30. Segal D. B. Theoretical basis for differentiation of ferric-iron bearing mi nerals, using Landsat MSS Data. Proceedings of Symposium for Remote Sensing of Environment, 2nd Thematic Conference on Remote Sensing for Exploratory Geology, Fort Worth, TX. 1982. pp. 949–951.
31. Rockwell B. W., Gnesda W. R., Hofstra A. H. Improved automated identification and mapping of iron sulfate minerals, other mineral groups, and vegetation using Landsat 8 Operational Land Imager Data, San Juan Mountains, Colorado, and Four Corners Region. US Geological Survey. 2021. No. 3466. DOI: 10.3133/sim3466
32. Orynbassarova E, Yerzhankyzy A, Shults R, Roberts K, Togaibekov A. Strategies of GNSS processing and measuring under various operational conditions. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2022. No. 3. pp. 146–150.
33. Akhmetov R., Makhmetova G., Orynbassarova E., Baltiyeva A., Togaibekov A. et al. The study of kinematic GNSS surveying for BIM georeferencing. The International Archives of the Photogrammetry, Remote Sensing and
Spatial Information Sciences. 2022. Vol. XLVI-5/W1-2022. pp. 7–14.

Полный текст статьи Analysis of mineral indices from remote sensing: a case-study of the Tokrau river
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