There are a lot of research related to mine exploration by using remote sensing techniques. Somaieh Afshari and his colleagues in 2015 investigated the extraction of geological faults using remote sensing data in the Kope Dagh area in the north of North Khorasan province, and the methods used in this research include the manual method which is automatic and semiautomatic on Landsat 8 satellite images. Hojjatole Ranjbar et al. (2009), with the topic of identifying and highlighting altered areas, determined the altered areas using satellite images with a scale of 1:100,000 in the Varkeh Rabat area of Kerman and prepared geological maps (al., (2009)). Safai Siyam and his colleagues in the training workshop (34th meeting and 2nd International Specialized Congress of Earth Sciences March 3-5, 2014 Tehran-Iran). In this research, the exploration of Sangan iron deposit was estimated using satellite data and magnetmetric. To highlight the areas containing iron oxide, principal component analysis methods, band ratio and regression least squares method were used on ASTER data images and field investigations were made to prone areas. To verify the results, the magnetic anomalies of Sangan iron deposit were drilled and acceptable results were obtained from the drilling samples (colleagues, 2014). Nabi Esadi Soheila and colleagues in (2014) investigated the alteration of Chagharat iron-apatite mine using satellite images and remote sensing methods. The analysis of satellite images of the Chagharat mineral region shows the areas containing iron oxides-hydroxides in the southwest of this region (Rasouli, 2014). Zahra Fanadi, in 2016, marketization of iron minerals was investigated using ASTER and Landsat ETM+ satellite images in Hanshek region of Fars province. By using ETM+ and ASTER images and using color combination techniques, band ratios, principal component analysis and directional filters, highlighting of iron-bearing areas, dolomite host rock and regional contours was done [23]. Seyed Kivan Esmaili and his colleagues investigated the efficiency of remote sensing in the detection of iron oxide (magnetite) in Golghar mining area in Sirjan city. In this research, the discovery and identification of the iron mine has been done using satellite images (Seyed Kivan Esmaili Ali Esmaili). Mostafa Haidari Javanmardi (2015), conducted a research on the exploration of mineral reserves and investigated the effectiveness of remote sensing in detecting iron oxide (magnetite), in the case study of Chadormello-Yazd mine, and prepared detailed maps of the iron ore situation in the region (Whattam, et.al 2023). Arnab Sengupta and his colleagues in identified and mapped the iron ore alteration zone with high potential in Jodha, located in Odisha, India, using ASTER and Hyperion satellite images. The algorithms used in this research are principal component analysis (PCA) and spectral angle mapper (SAM). In this research, SWIR and VNIR bands of ASTER data were used. The results show that the iron mineral, silicate minerals and iron oxide index have been determined on the ASTER satellite data and the alteration zones and iron minerals have been determined., The Kappa coefficient method has been used to evaluate the accuracy and precision. In this research, they have used the support vector machine (SVM) algorithm and the geochemical data of the orientation of iron ores in dry areas that exist (Mohcine Chakouri). dealt with the issue of identifying and mapping minerals using satellite images, and the algorithms used in this research are BR (Band Ration). The results of this research show that different clay and carbonate minerals were identified with ASTER SWIR band ratios. Also, the results show that ASTER can be well used for mapping and identification of iron ore and minerals. Farzaneh Mami and his colleagues in researched on the topic of mining exploration and identifying fault lines using satellite images. In this research, Lineament extraction algorithms, BR band ratio, PCA principal component analysis, SAM spectral angle method and fitting of spectral features have been used to map and create alteration layer related to mineralization.
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 Comprehensive Review of Remote Sensing Techniques in Iron Ore and Mineral Exploration
Integration of Remote Sensing and Spectral Data:
- Researchers often combine remote sensing data (such as satellite imagery) with spectral measurements and field verification to identify iron occurrences.
- Image processing techniques are applied to satellite data to discriminate iron-rich localities within study areas.
Case Study in Egypt:
- A case study in the Central Eastern Desert (CED) of Egypt focused on iron exploration. Researchers identified iron occurrences in metavolcanic rocks.
- Iron ore was found in the form of Banded Iron Formation (BIF), veins, and lenses. These occurrences mainly consisted of magnetite and hematite.
- Structural controls on iron ore deposition were also considered in the investigated areas.
Remote Sensing Techniques Used:
- Crosta Principal Component Analysis (CPCA): Helps discriminate iron-rich localities.
- Constrained Energy Minimization (CEM): A supervised classification technique for identifying iron-enriched regions.
- Landsat-8 Band Ratio (band6/band2): A newly proposed approach for accurate delineation of iron-enriched areas [1].
References
- 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
- Mineral Exploration methods Using Remote Sensing and GIS techniques: A Review https://techjournals.stmjournals.in/index.php/JoRSG/article/view/1391
- Shirmard, H., Farahbakhsh, E., Müller, R. D., & Chandra, R. (2022). A review of machine learning in processing remote sensing data for mineral exploration. Remote Sensing of Environment, 268, 112750.https://arxiv.org/pdf/2103.07678
