Discrimination of Rock Units in Karst Terrains Using Sentinel-2A Imagery

Abstract

We explored the potential incorporation of Sentinel-2A imagery for rock unit determination in the Croatian karst region dominated by carbonate rocks. The various lithological units are potential sources of both stone aggregates and dimension stone, and their spatial distribution is of high importance for mineral resource management. The presented approach included the preprocessing and processing of existing analog data (geological maps), Sentinel-2A satellite images and the United States Geological Survey spectral indices, all in combination with ground truth data. Geological mapping and digital processing of legacy maps using the K-means and random forest algorithm reduced the spatial error of the geometry of geological boundaries from 100 m and 300 m to below 100 m. The possibility of discriminating individual lithological units based on spectral analysis and discriminant function analysis was also examined, providing a tool for evaluating the geological potential for mineral resources. Despite the challenges posed by the lithological homogeneity of karst terrain, the results of this study show that the use of spectral signature data derived from Sentinel-2A satellite images can be successfully implemented in such terrains for the enhancement of existing geological maps and mineral resources exploration.

Keywords

• geological mapping
• Sentinel-2A
• K-means
• random forest
• discriminant function analysis