Mineral mapping and ore prospecting with HyMap data over eastern Tien Shan, Xinjiang Uyghur autonomous region

19Citations
Citations of this article
28Readers
Mendeley users who have this article in their library.

Abstract

Using HyMap data, mineral identification and mineral mapping were conducted on the basis of the spectral absorption index (SAI) and other spectral absorption features in a study area in Tudun, eastern Tien Shan. Alteration minerals, such as calcite, alumina-rich (Al-rich) muscovite, epidote, and antigorite, were explored, and their relative abundance was depicted. A cross-validation was performed, and it showed a high degree of consistency between the imagery results and the results of previous literature. To further validate the mineral mapping from HyMap data, a field survey was carried out and rock samples were collected for quantitative analysis using a Por Infrared Mineral Analyzer (PIMA) and the software affiliated with it. Minerals were discriminated, and their relative abundance was calculated from the spectra. Although we found that the absorption band-depth and SAI agreed well with each other and with the relative abundance of mineral alterations, the spectral absorption band-depth provided a better representation. Finally, ore prospecting of the study area was presented, and we found the distribution and close spatial relationships among the minerals extracted using the HyMap data. In the northern and northwestern part of the Gold-mine area, there was a mineralized muscovite alteration showing a sheet or block distribution. In the Copper-mine area, Al-poor muscovite with a sheet distribution was distributed in the north and northeast region, and Al-rich muscovite showed a block distribution enclosed by the distribution area of Al-poor muscovite. These all showed good ore prospects for the study area.

Cite

CITATION STYLE

APA

Huo, H., Ni, Z., Jiang, X., Zhou, P., & Liu, L. (2014). Mineral mapping and ore prospecting with HyMap data over eastern Tien Shan, Xinjiang Uyghur autonomous region. Remote Sensing, 6(12), 11829–11851. https://doi.org/10.3390/rs61211829

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free