Novel comprehensions of lithological and structural features gleaned via Sentinel 2 texture analysis

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.