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A New Vector for Mapping Gold Mineralization Potential and Proposed Pathways in Highly Weathered Basement Rocks using Multispectral, Radar, and Magnetic Data in Random Forest Algorithm

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Abstract

Various deformation events and weathering processes are among the obstacles to exploration of natural resources, especially mineral ones. This study addressed these obstacles by proposing solutions through the utilization of multiple multispectral, radar, and magnetic datasets. The study region, situated in a region between two blocks associated with the Arabian–Nubian Shield, is known for the presence of these obstacles. Also, the region is characterized by the conflicting nature of these blocks in relation to occurrences of gold mineralization. Various optical and multi-frequency radar datasets were used for detailed geological/mineralogical discrimination and surface lineaments mapping, respectively. Numerous composite enhancement, processing, and classification methods were applied to aeromagnetic and multispectral data to derive as much information as possible from these data. The results of the classification of minerals, the separation of rock units, and the identification of deep-seated geological structures were combined to produce a map for predicting gold prospectivity by generating a random forest model using 10 controlling factors and the previously defined zones of gold mineralization. A three-dimensional model was generated to show the locations of the expected gold mineralization potential areas with regard to depth in the investigated region. This model figured out the strong relation between gold potentialities related to their suggested pathways, particularly WNW- and N-trending shear zones. Our model indicates that the region is promising for mining activities and presents a new approach for mapping pathways of gold-mineralized–altered zones that can be applied worldwide.

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Acknowledgments

We would like to convey our heartfelt thanks to Dr. Mohammad Parsa (Geological Survey of Canada, Ottawa, Ontario K1A 0E8, Canada) for his valuable support throughout the research process.

Funding

No funding was received for conducting this study.

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Authors and Affiliations

  1. Department of Geology, Faculty of Science, Suez University, P.O. Box: 43221, Suez, Egypt

    Ahmed M. Eldosouky & Saada A. Saada

  2. Department of Civil and Environmental Engineering, Umm Al-Qura University, Makkah, Saudi Arabia

    Abdullah Othman

  3. Department of Geology, Faculty of Science, Zagazig University, P.O. Box: 44519, Zagazig, Egypt

    Sara Zamzam

Authors
  1. Ahmed M. Eldosouky
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  2. Abdullah Othman
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  3. Saada A. Saada
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Correspondence to Sara Zamzam.

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Appendix: (RST Calculations Using L8_OLI (B1-7) and TIR (B10, 11))

Appendix: (RST Calculations Using L8_OLI (B1-7) and TIR (B10, 11))

  1. (i)

    Reflectance and normalized difference vegetation indices (NDVIs) were calculated using DNs of L8_OLI optical bands in the following equation:

$${\text{NDVI}} = \frac{{{\text{NIR}} - {\text{RED}}}}{{{\text{NIR}} + {\text{RED}}}}$$
  1. (ii)

    The minimum and maximum NDVI values were utilized for the proportion of vegetation calculations, thus:

    $${\text{Pv}} = \left[ {\frac{{{\text{NDVI}} - {\text{NDVI}} _{\min } }}{{{\text{NDVI}} _{\max } + {\text{NDVI}} _{\min } }}} \right]^{2}$$
  2. (iii)

    Pv values were employed to calculate rock surface emissivity (e) as:

    $$e = 0.004*{\text{Pv}} + 0.986$$
  3. (iv)

    Radiance and brightness temperature (BT) were computed separately from L8_OLI/TIRS thermal bands (10 and 11) using radiometric calibration tool.

  4. (v)

    RST estimation as:

    $${\text{RST}} = \frac{{{\text{BT}}_{c} }}{{1 + \left[ {\frac{{W*{\text{BT}}_{c} }}{14380}} \right]\ln \left( e \right)}}$$

    where BTc is BT subtracted by 273.15 and w is the emitted radiance’s wavelength.

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Eldosouky, A.M., Othman, A., Saada, S.A. et al. A New Vector for Mapping Gold Mineralization Potential and Proposed Pathways in Highly Weathered Basement Rocks using Multispectral, Radar, and Magnetic Data in Random Forest Algorithm. Nat Resour Res 33, 23–50 (2024). https://doi.org/10.1007/s11053-023-10292-3

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