Using Landsat-8 Satellite Data to Predict Ore Mineralization for the Northern Territories by the Example of the Central Part of the Maloural’skaya Zone (the Polar Urals)

• Published in: Izvestiya. Atmospheric and oceanic physics Vol. 59; no. 9; pp. 1055 - 1069
• Main Authors: Ivanova, J. N., Nafigin, I. O.
• Format: Journal Article
• Language: English
• Published: Moscow Pleiades Publishing 01.12.2023; Springer Nature B.V
• Subjects: Climatology; Copper; Data analysis; Data processing; Density; Earth and Environmental Science; Earth Sciences; Fault lines; Fuzzy logic; Fuzzy sets; Geochemistry; Geologic mapping; Geological mapping; Geological maps; Geology; Geophysics/Geodesy; Global positioning systems; Gold; GPS; Landsat; Localization; Mineral resources; Mineralization; Mineralogy; Principal components analysis; Remote sensing; Satellite data; Spacecraft; Statistical analysis; Use of Space Information about the Earth Geophysical and Geological Research from Space; polymetallic ore occurrences; Landsat-8; manual and automatic lineament extraction; fuzzy logic; morphostructural map; the Polar Urals; lineament density analysis; remote sensing data processing; satellite images
• ISSN: 0001-4338; 1555-628X
• DOI: 10.1134/S0001433823090098

In the course of this study, an approach is developed focused on identifying probabilistic zones of increased fracturing (areas with a high density of lineaments), considered a predictive sign for the localization of ore mineralization in the central part of the Maloural’skaya zone (the Polar Urals). This area is promising for the detection of polymetallic-type ore occurrences (Fe, Cu, Cu-Zn, and Au-Cu). Predictive schemes for the distribution of highly permeable rock zones are constructed and promising areas for polymetallic mineralization are identified based on this approach, accounting for the geological information, the distribution of mineral resources, remote sensing data and the results of their processing, and the lineament density schemes. The remote sensing data processing is based on the identification of structures by manual and automatic methods and their integration based on fuzzy logic. Morphostructural maps obtained from the Landsat-8 spacecraft data show that ore occurrences of polymetallic specialization known in the area are located along the perimeter of a large morphostructure of the first order, as well as near radial structures up to 20 km in length in the NE and (less often) in the NW direction. As a result of a comparison of remote sensing data with the geological map of the study area and known ore occurrences, six promising zones are identified. The contoured areas show spatial consistency with several known polymetallic ore occurrences localized in the study area.