Skip to main content
U.S. flag

An official website of the United States government

Hyperspectral remote sensing of white mica: A review of imaging and point-based spectrometer studies for mineral resources, with spectrometer design considerations

April 9, 2022

Over the past ~30 years, hyperspectral remote sensing of chemical variations in white mica have proven to be useful for ore deposit studies in a range of deposit types. To better understand mineral deposits and to guide spectrometer design, this contribution reviews relevant papers from the fields of remote sensing, spectroscopy, and geology that have utilized spectral changes caused by chemical variation in white micas. This contribution reviews spectral studies conducted at the following types of mineral deposits: base metal sulfide, epithermal, porphyry, sedimentary rock hosted gold deposits, orogenic gold, iron oxide copper gold, and unconformity-related uranium. The structure, chemical composition, and spectral features of white micas, in this contribution defined as muscovite, paragonite, celadonite, phengite, illite, and sericite, are given. Reviewed laboratory spectral studies determined that shifts in the position of the white mica 2200 nm combination feature of 1 nm correspond to a change in Aloct content of approximately ±1.05%. Many of the reviewed spectral studies indicated that a shift in the position of the white mica 2200 nm combination feature of 1 nm was geologically significant.

A sensitivity analysis of spectrometer characteristics; bandpass, sampling interval, and channel position, is conducted using spectra of 19 white micas with deep absorption features to determine minimum characteristics required to accurately measure a shift in the position of the white mica 2200 nm combination feature. It was determined that a sampling interval 

Publication Year 2022
Title Hyperspectral remote sensing of white mica: A review of imaging and point-based spectrometer studies for mineral resources, with spectrometer design considerations
DOI 10.1016/j.rse.2022.113000
Authors John Meyer, Elizabeth Holley, Raymond Kokaly
Publication Type Article
Publication Subtype Journal Article
Series Title Remote Sensing of Environment
Index ID 70237059
Record Source USGS Publications Warehouse
USGS Organization Geology, Geophysics, and Geochemistry Science Center
Was this page helpful?