Iron ore Streaks Simultaneously by Using Remote Sensing Technique : A Part from the Book Chapter : Identification of Iron Ore Mine and Structural Lineaments Extraction by Using Remote Sensing Technique, Iran: A Case Study of the Sangan Khaf Iron Ore Mine

Fault Line Extraction

Finally, the method was used to show the fault lines, which were extracted using ASTER and Landsat-8 satellite images. Shovan Lal Chattoraj, discussed the importance of remote sensing in mineral exploration in potential iron ore-rich areas. In this research, the integration of remote sensing, gravity and geochemical data for iron ore exploration in Alwar Basin, Rajasthan, India has been researched. Nazi Mazhari, used satellite images and airborne geophysical data on the topic of identification and mapping of iron ore types in Sangan mining area in Iran. The results were confirmed by geological mapping and comprehensive field work, and this integration model can be extended to other arid and semiarid regions with iron potential at both regional and regional scales. Hooman Moradpour, on the topic of using satellite remote sensing images for mineral exploration is a fast and low-cost approach to indicate high potential areas. In this research, Landsat-7 and ASTER remote sensing satellite images have been used to identify iron minerals in the study areas. There are no updated study about fault exploration and demonstration the relation between soil salinity and presence of iron ore streaks simultaneously by using remote sensing technique in this unique study area.

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.


Also See :  These Communities Face Persistent Challenges from Flood and Riverbank Erosion : A Part from The Book : Living with Floods in Bangladesh’s Riverine Islands: Understanding Vulnerability and Resilience


Recent global research developments in Remote Sensing Techniques for Iron Ore Mine Detection

Rapid Detection of Iron Ore and Mining Areas:

  • A recent study proposed a method for total iron content (TFE) detection based on reflectance spectroscopy and remote sensing.
  • Here are the key points from that research:
  • Spectral Experiments: Iron ore samples were analyzed using an HR SVC-1024 spectrometer to obtain spectral data.
  • Data Processing: Spectra were smoothed and dimensionally reduced using wavelet transform and principal component analysis.
  • Detection Model: An improved sparrow search algorithm and batch normalization-optimized MSSA-BNVTELM (two hidden layer extreme learning machine) achieved superior TFE detection accuracy.
  • Remote Sensing Model: Sentinel-2 data combined with MSSA-BNVTEM was used to detect TFE distribution in mining areas.
  • Results: The remote sensing approach successfully identified TFE distribution, facilitating mining planning.

Other Techniques:

References

  1. 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
  2. Xu M, Mao Y, Zhang M, Xiao D, Xie H. Rapid Detection of Iron Ore and Mining Areas Based on MSSA-BNVTELM, Visible—Infrared Spectroscopy, and Remote Sensing. Remote Sensing. 2023; 15(16):4100. https://doi.org/10.3390/rs15164100
  3. Ciampalini, A., Garfagnoli, F., Antonielli, B. et al. Remote sensing techniques using Landsat ETM+ applied to the detection of iron ore deposits in Western Africa. Arab J Geosci 6, 4529–4546 (2013). https://doi.org/10.1007/s12517-012-0725-0

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