Comparison of Original and Deep-Learning Enhanced Sentinel-2 Imagery in Mineral Prospecting Problems

Remote sensing methods based on satellite data with open access (as Sentinel-2 provides) are commonly used in geological applications. This paper examines whether Sentinel data with artificially enhanced resolution (to 2.5 m of 8 bands) can provide higher-quality results with mineral prospecting analysis. We believe that we have found deep-learning enhanced data to be the basis for getting considerably more valuable results. Furthermore, the enhanced resolution data allowed for an average of 8.55% more coverage, with the test area to be highlighted. We anticipate our research to be a starting point for the broader use of enhanced imagery in geological mapping.