Mapping the Jurassic/Cretaceous lithological units in the Buëch area in France using Sentinel-2 and ASTER

Abstract

Spaceborne remote sensing performs a significant role today in geological mapping, interpretation and analysis of large areas in a rapid and cost-efficient manner. Spaceborne satellite imagery have been successfully utilized in lithological mapping of arid areas, however, similar approaches for lithological mapping in semi-arid regions with high degree of structural complexity, vegetation and topographic effects are yet to be developed. The primary objective of this study is to combine field-based spectroscopic research with geological remote sensing in obtaining representative lithological maps of the Buëch area in South-East France. To achieve this aim Support Vector Machine (SVM) classifier and Spectral Angle Mapper (SAM) were used on Sentinel-2 and ASTER imagery. Spectroscopic examination of field samples enabled the creation of spectral endmembers representative for the area and detection of local weathering mechanisms. The results derived from SVC classifier showed great pattern-recognition ability and more accurate classification of different lithological groups. SAM derived thematic mapper demonstrated the ability to correctly classify a great portion of blue marl outcrops, by recognising the lack of spectral response displayed by blue marls as being the distinctive indicator of the class. Using and evaluating different satellite imagery shows that Sentinel-2 allows better mapping in this semi-arid area, indicating that the higher spatial resolution of Sentinel-2 has an edge over the higher spectral resolution in the SWIR range of ASTER for this specific setting and methodology. The study has shown that field-based spectroscopic research complements geological remote sensing well. The limiting factor in achieving better classification is the spectral and spatial properties of the satellite imagery. Therefore, future research should consider the integration of hyperspectral data and assimilation of geomorphic products to increase the accuracy of lithological unit discrimination.