Remote sensing is the science of obtaining information about objects and phenomena on the surface of the earth without direct contact with them and its records the interaction between matter and electromagnetic energy (Armin Moghimi, 2014). This process has been used in many important remote sensing applications, such as agriculture, geology, vegetation changes and forestry, mapping and urban planning, event registration and pollution (Pour and Hashim, 2012). By receiving the information of the stones minerals can be explored with remote sensing techniques. In this research, an attempt has been made to investigate the method of obtaining information and characteristics of iron minerals. Stones and minerals are used as important and useful tools for the development of human life from our prehistoric period to the rise of civilization until today. Due to having a heterogeneous crust and the influence of various geological events in the formation of the crust, the land of Iran is rich in minerals. Mineral exploration in Iran started officially in 1939 in a scientific and continues way (Hossein, 2033). One of the most basic issues in mines is exploration. Today, conducting exploratory studies using modern methods and technologies is one of the study priorities in the countries of the world. Various satellites have been launched for the needs of geology and its studies. The topic of mining exploration includes four main stages: prospecting, preliminary exploration, detailed exploration, and supplementary (extractive) exploration. There are also methods for exploring mines, which include exploratory geochemical methods, exploratory geophysical methods, exploratory drilling and aerial methods (remote sensing). Spectral behavior of minerals over time is the most important factor in using satellite images to identify mines. Spectral behavior means spectral characteristics and nature of minerals. As stated, considering the importance of iron mining and its economic value, the identification of iron minerals using satellite images is one of the active and ongoing issues in the field of remote sensing, due to the precise visibility of satellites in the discovery of mine. Image classification methods are divided into 3 groups: supervised classification methods, unsupervised classification methods, and object-oriented classification methods. Unsupervised algorithms are of interest to many researchers due to their simplicity and high variety of algorithms. These algorithms are widely used in mining exploration using aerial and satellite images.
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 Advanced Remote Sensing Techniques for Iron Ore Identification and Mineral Analysis
Remote Sensing Techniques for Iron Ore Identification:
- Integration of Spectral Data: Researchers often integrate remote sensing data (such as satellite imagery) with spectral measurements and field verification to identify iron occurrences.
- Image Processing Techniques: Various image processing techniques are applied to satellite data. For instance:
- Crosta Principal Component Analysis (CPCA): This method helps discriminate iron-rich localities within study areas.
- Constrained Energy Minimization (CEM): Another supervised classification technique used to identify iron-enriched regions.
- Landsat-8 Band Ratio (band6/band2): A newly proposed approach for accurate delineation of iron-enriched areas [1].
- Mineral Signatures: Researchers analyze spectral signatures of iron minerals (such as magnetite and hematite) and host rocks to detect iron occurrences.
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 using remote sensing techniques. The iron ore was found in the form of Banded Iron Formation (BIF), veins, and lenses. These occurrences were mainly composed of magnetite, hematite, and other minerals. The study also considered the structural controls on iron ore deposition [2].
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
- Surface Mineral Allocation and Lithological Mapping Based on Remote Sensing
https://www.mdpi.com/journal/remotesensing/special_issues/Mineral_Lithological - Tagwai, M.G., Jimoh, O.A., Shehu, S.A. and Zabidi, H. (2024), “Application of GIS and remote sensing in mineral exploration: current and future perspectives”, World Journal of Engineering, Vol. 21 No. 3, pp. 487-502. https://doi.org/10.1108/WJE-09-2022-0395
- New Trends on Remote Sensing Applications to Mineral Deposits
https://www.mdpi.com/journal/remotesensing/special_issues/new_trends_remote_sensing_applications_mineral_deposits
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