Detecting subtle alteration information from ASTER data using a multifractal-based method: A case study from Wuliang Mountain, SW China

Abstract

Remote sensing has been widely used to interpret hydrothermal alteration zones and it can support the geological field mapping, which is very useful for mineral exploration in inaccessible regions. However, the alteration information in covered terrains is usually not strong enough to be detected using traditional remote sensing methods, so how to efficiently detect subtle alteration information remains a challenging task. In this study, the multifractal theory-based Spectrum-Area (S-A) method is used for the processing of remote sensing data and the new method of “Principal Component Analysis (PCA) + S-A” is proposed as a tool to interpret hydrothermal alteration beneath covered areas. In order to test the efficiency of this method, the “PCA + S-A” method was compared with the traditionally used PCA method based on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. The Wuliang Mountain in the Yunnan Province of SW China, a rugged terrain with high altitudes and dense vegetation coverage, was selected as a case study to detect information on chlorite, epidote, biotite, and muscovite alteration, respectively. The following field survey and petrographic studies reveal that: (1) the average detection accuracy of the “PCA + S-A” method is 90.80%, 9.34% higher than that of the PCA method; (2) in the covered areas where the traditional PCA method cannot detect any subtle hydrothermal alteration, the “PCA + S-A” method can be successfully applied; and (3) in those areas where the fractional vegetation cover (FVC) is greater than 0.8, the detection of subtle hydrothermal alteration using the proposed method is inefficient, which requires further studies.