Mapping Hydrothermal Zoning Pattern of Porphyry Cu Deposit Using Absorption Feature Parameters Calculated from ASTER Data

• Published in: Remote sensing (Basel, Switzerland) Vol. 11; no. 14; p. 1729
• Main Authors: Wu, Mengjuan, Zhou, Kefa, Wang, Quan, Wang, Jinlin
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 2019
• Subjects: Absorption; absorption feature parameters; Aluminum; ASTER; ASTER (radiometer); Bands; Bearing; Computer simulation; Copper; Curve fitting; Geologic mapping; Geological mapping; Geology; hydrothermal zoning pattern; Iron; Laboratories; Magnesium; Mapping; Mineral resources; Mineralization; Minerals; Parameter identification; Porphyry copper; porphyry Cu deposit; Principal components analysis; Remote sensing; Rocks; Short wave radiation; Spectra; Statistical methods; Thermal emission; Zoning; Argentina; United States > US; China; Japan
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs11141729

Identifying hydrothermal zoning pattern associated with porphyry copper deposit is important for indicating its economic potential. Traditional approaches like systematic sampling and conventional geological mapping are time-consuming and labor extensive, and with limitations for providing small scale information. Recent developments suggest that remote sensing is a powerful tool for mapping and interpreting the spatial pattern of porphyry Cu deposit. In this study, we integrated in situ spectral measurement taken at the Yudai copper deposit in the Kalatag district, northwestern China, information obtained by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), as well as the spectra of samples (hand-specimen) measured using an Analytical Spectral Device (ASD) FieldSpec4 high-resolution spectrometer in laboratory, to map the hydrothermal zoning pattern of the copper deposit. Results proved that the common statistical approaches, such as relative band depth and Principle Component Analysis (PCA), were unable to identify the pattern accurately. To address the difficulty, we introduced a curve-fitting technique for ASTER shortwave infrared data to simulate Al(OH)-bearing, Fe/Mg(OH)-bearing, and carbonate minerals absorption features, respectively. The results indicate that the absorption feature parameters can effectively locate the ore body inside the research region, suggesting the absorption feature parameters have great potentials to delineate hydrothermal zoning pattern of porphyry Cu deposit. We foresee the method being widely used in the future.