Improving the accuracy of hydrothermal alteration mapping based on image fusion of ASTER and Sentinel-2A data: a case study of Pulang Cu deposit, Southwest China

Abstract

Mapping hydrothermal alteration is an important means of mineral exploration, therefore, effective improvement of the accuracy of identification of hydrothermal alteration minerals is a hot topic. In this study, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Sentinel-2A data were selected for the Pulang copper deposit, to improve the accuracy of hydrothermal alteration mineral mapping. Three data fusion methods of Principal Component Analysis (PCA), Gram–Schmidt (GS) and High-Pass Filtering (HPF) were employed, and method of spectral matching was introduced to obtain high spatial resolution and high spectral fidelity fused data. The comparison showed that the HPF fusion method had the best effect. The fused data by the HPF fusion method were then implemented to map hydrothermal alteration minerals by using a multifractal-based method of PCA + Spectrum–Area. Through the verification of a field investigation, the results exhibited a similar hydrothermal alteration distribution, compared with the results obtained from the original ASTER data, but with higher identification accuracy. Therefore, the case study strongly suggests that the image fusion method with spectral matching is an effective tool to increase spatial resolution, while maintaining high spectral fidelity. Thus, it is a valuable and economic method for improving the identification accuracy of hydrothermal alteration minerals. HIGHLIGHTS The spectral matching method was introduced to unify the surface reflectance of ASTER and Sentinel-2A data. Principal Component Analysis (PCA), Gram-Schmidt (GS) and High-Pass Filtering (HPF) methods were employed to fuse AST ER and Sentinel-2A data. The results show that the extraction accuracy of hydrothermal alteration minerals based on AST ER - Sentinel-2A fused data has 6.98% higher than that of original ASTER data.