However, these deposits tend to be found in clusters so that additional orebodies may exist deep below the known deposits. While the exploitation of the surficial deposits has a long history, with the development of high-precision and successful methods for mineral exploration, the geophysical techniques had a low success rate and suffered from limitations, such as the small size of chromite pods, the physical similarities with certain rocks, structural features, and presence of iron-rich bodies Most surficial podiform chromite deposits have been exploited due to their resistance to weathering compared to their serpentinized host, which allows them to stand higher than the surrounding rocks. The results of our work highlight the potential of multi-scale satellite and UAV-based remote sensing to find footprints of some chromite mineral deposits. This is particularly true at the contact with mafic dykes, akin to some worldwide chromite deposits. The serpentinite with probable dunitic protolith, discriminated for a peculiar Fe-rich Ni-bearing lateritic crust, is more productive for chromite prospecting. Based on their presumed protolith, the highly serpentinized ultramafics and serpentinites were classified into two main categories (dunite or harzburgite). All ultramafic units were classified into four groups based on the degree of serpentinization, represented by the intensity of their average spectral reflectance. The validation of the results was performed through a second phase, made up of field mapping, sampling, chemical analysis, and microscopic studies, leading to the discovery of new chromite occurrences and mineralized zones. The combination of visual interpretation and supervised classification by machine learning methods yielded the production of a geological map, in which the lithological units and structures are outlined, including the crust-mantle transition zone units, mafic cumulates, crosscutting dykes, and mantle sequences. Results have been verified by an initial on-field checking and compared with the high-resolution (GSD ~6 cm) orthomosaic images obtained by the processing of photographs taken from an Unmanned Aerial Vehicle (UAV) at a promising area of 35 km 2.
The integration of satellite images coupled with change detection, band rationing, and target detection algorithms were used to distinguish potential lithological units hosting chromites. The case study is the area of the Sabzevar Ophiolite (NE Iran), which hosts several known chromite and other mineral deposits.
This research combines several remote sensing methods to discriminate the highly serpentinized peridotites hosting chromite pods from the other barren ultramafic and mafic cumulates.
The irregular and sporadic occurrence of chromite pods in podiform chromite deposits (PCD), especially in mountainous terranes with rough topography, necessitates finding innovative methods for reconnaissance and prospecting.
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