Testing ASTER and Sentinel-2 MSI Images to Discriminate Igneous and Metamorphic Rock Units in the Chadormalu Paleocrater, Central Iran

In the last fifty years, satellite images have been used to map the Earth's surface at a variety of scales. Two satellite multispectral sensors (Sentinel-2 MSI and ASTER) have great utility for lithological discrimination in areas of good rock exposures. This study was conducted in order to test the ability of these sensors to discriminate igneous and metamorphic lithologies in the Chadormalu paleocrater and evaluate the image types and processing methodologies. The MNF (Minimum Noise Fraction) transform, Mathematical Evaluation Method (MEM), Spectral Angle Mapper (SAM), Mixture Tuned Matched Filter (MTMF), and band ratios were performed on near and short wave infrared ASTER and Sentinel-2 bands. Comparison of the results from several methods demonstrates that the MEM method can detect lithological units with very low false detection and better matching with ground truth data. Moreover, this study indicates that the results produced by the MEM algorithm on Sentinel-2 MSI data are more accurate than the results produced with ASTER data in the same area. Therefore, the MEM algorithm seems to be well suited for image classification involving multispectral databases such as ASTER and Sentinel-2 images.

Automated summary

This study tested the ability of satellite sensors like Sentinel-2 MSI and ASTER to discriminate igneous and metamorphic lithologies in the Chadormalu paleocrater, with the MEM method proving to be the most accurate. The results suggested that the MEM algorithm is well suited for image classification involving multispectral databases like ASTER and Sentinel-2 images.