article · Ore Geology Reviews
Geological mapping is critical for mineral prospecting and infrastructure development, yet standard remote sensing methods often face difficulties with data dimensionality, requiring substantial time to select and process multiple spectral bands. A new approach applies texture analysis to single bands from Sentinel 2 and ALOS PRISM satellite datasets to identify rock types and complex structural features. By testing varied pixel sizes and kernel dimensions, the technique successfully differentiates rock units, quaternary deposits, and systematic rock bodies while resolving folds, faults, joints, and foliations. Verified through intensive fieldwork, petrographical analysis, and comparisons with existing geological maps, this method demonstrates that single-band second-order statistics can replace time-consuming multi-band workflows. It substantially reduces the time and effort needed for surface investigations by accentuating both microscale and mesoscale geological structures.
Traditional remote sensing for geological exploration requires analysing vast amounts of complex spectral data. Simplifying this workflow to a single satellite band while maintaining structural and rock-type clarity saves computational time and resources. This makes preliminary surveys faster, more accessible, and less costly, helping geologists rapidly pinpoint areas of interest before deploying intensive on-the-ground survey teams.
This approach is an applied and tested method relevant to mineral exploration companies, civil engineering firms, and geological survey organisations. By enabling rapid structural mapping and rock discrimination from single-band satellite data, it can serve as an efficient screening tool prior to field campaigns. Because the methodology has already been validated against ground data and petrographical samples, it appears close to adoption within existing remote sensing and GIS exploration workflows.
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Detailed geological mapping is the decisive key for mineral deposit prospecting, deciphering tectonic models, and outlining the main framework for most development programs and constructions. Without a doubt, various remote sensing datasets have introduced reliable lithological and structural mapping solutions. The main defect with remote sensing data is the curse of dimensionality, especially with hyperspectral data, where a lot of time is spent handling and selecting representative bands for various geological analyses. Consequently, and for the first time, our research is an attempt to resolve the complicated structural patterns (lineaments, folds, foliations, and cross-cutting relationships) and enhance lithological discrimination using a single band (of Sentinel 2 and ALOS PRISM data) and textural analysis. Through several trials over different pixel sizes (2.5 m and 10 m) and various kernels (3 × 3, 7 × 7, or 11 × 11), reasonable results are obtained, enabling lithological discrimination, in-depth structural analysis (foliations, faults, joints, and folds), shape recognition of systematic rock bodies, and delineation of quaternary deposits using single band analysis rather than time-consuming multiple band processing. Our results have been verified using intensive fieldwork and accurate visual interpretations using different datasets (e.g., previous geological maps, remote sensing data, etc.). Upon field verification and petrographical investigations of this research outcomes, we strongly recommend the adopted approach for the geological community, as it opens the doors for various applications utilizing single-band second-order statistics. We expect that this research could significantly help the geological community by reviving several previous studies and being applicable for future research, besides offering a reasonable approach for minimizing the time and efforts required for detailed field studies by highlighting micro- and mesoscale structures.
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DOI: 10.1016/j.oregeorev.2024.106068
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