THE MIDINFRARED REFLECTANCE OF MINERAL MIXTURES (7-14-MU-M)

Citation
Jl. Thomson et Jw. Salisbury, THE MIDINFRARED REFLECTANCE OF MINERAL MIXTURES (7-14-MU-M), Remote sensing of environment, 45(1), 1993, pp. 1-13
Citations number
38
Categorie Soggetti
Environmental Sciences","Photographic Tecnology","Geosciences, Interdisciplinary","Metereology & Atmospheric Sciences
ISSN journal
00344257
Volume
45
Issue
1
Year of publication
1993
Pages
1 - 13
Database
ISI
SICI code
0034-4257(1993)45:1<1:TMROMM>2.0.ZU;2-0
Abstract
There is growing interest in the mid-infrared spectral region (8-14 mu m) as both a laboratory and a remote sensing tool in geology, because this portion of the spectrum contains the characteristic, fundamental, molecular vibration bands for silicates and other mineral groups. How ever, it is necessary to understand the relationship between the spect ra of mineral mixtures and those of individual minerals in the mixture in order to completely interpret and predict mineral abundances from infrared data. Results of this study show quantitatively for the first time that the spectra Of particulate mixtures of silicate minerals in this wavelength region combine linearly by volume within a very small error, as long as particles are much larger than the wavelength so th at volume scattering is insignificant compared to surface scattering. Results here apply specifically to mineral samples in the 75-250 mum s ize range. They imply that we can predict the spectral response of a r ock if the constituent minerals and their abundances are known. More i mportantly, our results indicate that the relative quantities of miner als in simple mixtures can be predicted to within 12% in the worst cas e, and more typically to within 5%. Consequently, geologists should be able to unmix the composite spectra Of rocks to determine mineral abu ndances. This is important for both laboratory rock identification and remote sensing applications. By better understanding how component mi neral spectra mix in the spectrum of a rock, we can also better choose spectral band positions and resolutions in infrared remote sensing fo r compositional identification.