In recent decades, the world’s space technologies in the field of remote sensing satellites have grown and expanded significantly. Remote sensing has provided many applications in the exploration of mines and various mineral deposits. In this research, an attempt has been made to investigate the method of obtaining information and characteristics of iron minerals. The study area of the research is the Sangan mine, the largest iron ore mine in West Asia, and the images used in this research are related to the ASTER sensor. The spectral behavior of the soil is processed, and by using band ratio algorithms, the spectral behavior of each iron mineral is extracted. The areas that contain iron ore can be visually observed and analyzed. Among the spectral indices used in this research are Fe+3 – Fe+2 – Laterite – Gossan – Ferrous silicates – Ferric oxides, and the algorithms of these indices are implemented in the Google Earth Engine web system. After estimating the iron minerals, according to the output obtained from the spectral indices of iron, the results showed that in the last 19 years, the amount of iron ore in the Sangan region has been decreasing. The highest amount of iron minerals is related to the areas of the Sangan mineral complex and the central areas of the Sangan mountain. The map of the structutal lineamentss in the study area was carried out using the accuracy assessment for the correctness of iron ore calculations by the structural lineaments map and the output of the Ferrous silicates index, and the RMSE shows about 0.14%, which indicates that the accuracy of the iron ore is acceptable.
Author(s) Details:
Sajad Mehri
Islamic Azad University South Tehran Branch, Iran.
Sara Vahidi
Islamic Azad University South Tehran Branch, Iran.
Vahid Hatamzadeh
Islamic Azad University South Tehran Branch, Iran.
Paniz Nouri
Islamic Azad University South Tehran Branch, Iran.
Afshin Afshinfar
Islamic Azad University South Tehran Branch, Iran.
Ahmad Pourheidari
Islamic Azad University South Tehran Branch, Iran.
Amir Shahrokh Amini
Islamic Azad University South Tehran Branch, Iran.
Recent Global Research Developments in Iron Ore Mines Using Remote Sensing
Fault-Based Geological Lineaments Extraction:
- In a comprehensive review, researchers explored state-of-the-art remote sensing techniques and datasets for geological lineament analysis. These lineaments serve as indicators of tectonic units associated with mineral formation, active faults, groundwater control, earthquakes, and geomorphology.
- Optical remote sensing data from the Landsat series, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and Sentinel-2 are commonly used for lineament detection. Additionally, radar data from sources like Shuttle Radar Topography Mission (SRTM), Synthetic-aperture radar (SAR), Interferometric synthetic aperture radar (InSAR), and Sentinel-1 contribute to identifying geological lineaments.
- However, achieving consistent results remains a challenge due to variations in data acquisition and processing methods. Integrating manual and automated algorithms is often necessary to improve accuracy [1].
Application of Remote Sensing Techniques for Iron Ore Identification:
- Researchers applied various remote sensing methods, including Crosta principal component analysis (CPCA), constrained energy minimization (CEM), and a Landsat-8 band ratio (band6/band2), to discriminate iron-rich localities within study areas. These techniques aid in identifying iron ore deposits [2].
Lithological Discrimination and Structural Lineaments Extraction:
- A study focused on the Tiwit region (Jbel Saghro) using Landsat 8 and ASTER imagery. Researchers successfully discriminated lithological units and extracted structural lineaments, contributing to our understanding of the geological setting [3].
References
- Ahmadi, H., & Pekkan, E. (2021). Fault-based geological lineaments extraction using remote sensing and GIS—a review. Geosciences, 11(5), 183. https://mdpi-res.com/d_attachment/geosciences/geosciences-11-00183/article_deploy/geosciences-11-00183-v2.pdf?version=1619602857
- Ghoneim, S.M., Salem, S.M., El-Wahid, K.H.A. et al. Application of remote sensing techniques to identify iron ore deposits in the Central Eastern Desert, Egypt: a case study at Wadi Karim and Gabal El-Hadid areas. Arab J Geosci 15, 1596 (2022). https://doi.org/10.1007/s12517-022-10871-3
- Marzouki, A., Dridri, A. Lithological discrimination and structural lineaments extraction using Landsat 8 and ASTER data: a case study of Tiwit (Anti-Atlas, Morocco). Environ Earth Sci 82, 125 (2023). https://doi.org/10.1007/s12665-023-10831-4
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