Lithological discrimination of the mafic-ultramafic complex, Huitongshan, Beishan, China: Using ASTER data

Abstract

The Beishan area has more than seventy mafic-ultramafic complexes sparsely distributed in the area and is of a big potential in mineral resources related to mafic-ultramafic intrusions. Many mafic-ultramafic intrusions which are mostly in small sizes have been omitted by previous works. This research takes Huitongshan as the study area, which is a major district for mafic-ultramafic occurrences in Beishan. Advanced spaceborne thermal emission and reflection radiometer (ASTER) data have been processed and interpreted for mapping the mafic-ultramafic complex. ASTER data were processed by different techniques that were selected based on image reflectance and laboratory emissivity spectra. The visible near-infrared (VNIR) and short wave infrared (SWIR) data were transformed using band ratios and minimum noise fraction (MNF), while the thermal infrared (TIR) data were processed using mafic index (MI) and principal components analysis (PCA). ASTER band ratios (6/8, 5/4, 2/1) in RGB image and MNF (1, 2, 4) in RGB image were powerful in distinguishing the subtle differences between the various rock units. PCA applied to all five bands of ASTER TIR imagery highlighted marked differences among the mafic rock units and was more effective than the MI in differentiating mafic-ultramafic rocks. Our results were consistent with information derived from local geological maps. Based on the remote sensing results and field inspection, eleven gabbroic intrusions and a pyroxenite occurrence were recognized for the first time. A new geologic map of the Huitongshan area was created by integrating the results of remote sensing, previous geological maps and field inspection. It is concluded that the workflow of ASTER image processing, interpretation and ground inspection has great potential for mafic-ultramafic rocks identifying and relevant mineral targeting in the sparsely vegetated arid region of northwestern China.

Keywords

mafic-ultramafic complex / ASTER data / band ratio / minimum noise fraction / mafic index / principal component analysis

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