The depth of the iron deposit along with its shape, grade and available equipment have an effect on the way of iron extraction. In the iron production stages section, we will introduce the methods of iron extraction. The first step in the process of iron production is to find places where there is a possibility of placing high grade iron ore. In this way, before extracting iron, its mineral reserves should be discovered first. The purpose of this research was to identify iron ore mines by using the unsupervised implementation of algorithms in the space of Google Earth Engine system. To implement the relationships in this research, Landsat and Esther images are used and are related to several recent years from different months of the year, only the important point is choose the best images for image processing. The main method in this research is based on the analysis of the spectral behavior of surface phenomena that are used to identify iron minerals.
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 Revolutionizing Iron Ore Exploration: Remote Sensing’s Impact on Mine Discovery
Application of Remote Sensing for Mineral Resource Exploration and Exploitation:
- This special issue in the journal Minerals focuses on the application of remote sensing technology in mining. It covers topics such as mineral identification, geological mapping, alteration anomaly zoning, and prospecting prediction. The goal is to contribute to the sustainable development of the global mining industry.
Mapping Iron Ore Deposits Using Remote Sensing Techniques:
- Researchers have applied various remote sensing techniques to identify iron-rich localities. These include methods like Crosta principal component analysis (CPCA), constrained energy minimization (CEM), and Landsat-8 band ratio (band6/band2). These techniques help discriminate iron ore deposits within study areas [1].
Monitoring Iron Ore Stopes with Hyperspectral Remote Sensing:
- A novel method combines hyperspectral remote sensing and ground data to monitor and map changes in iron ore stopes. The approach utilizes a 3D convolutional neural network and fusion data for accurate monitoring [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
- Xiao, D., Vu, Q.H., Le, B.T. et al. A method for mapping and monitoring of iron ore stopes based on hyperspectral remote sensing-ground data and a 3D deep neural network. Neural Comput & Applic 35, 12221–12232 (2023). https://doi.org/10.1007/s00521-023-08353-y