RESUMEN
In order to explore the intrinsic relationship of mineral spectral characteristics and its composition, and provide the basis for the detection of mineral micro information by using hyperspectral technology, based on the thinsection analysis, the authors identified the minerals characteristics and mineral assemblages in rock samples, delineated typical chlorite minerals and divided the occurrence characteristics of chlorite. The authors measured chemical composition of 146 typical chlorite mineral particles by using electron probe micro analysis technology, and calculated the relevant chemical parameters of n(Al(IV)), n(Al(VI)), n(Fe), n(Mg), and n(Fe)/n(Fe + Mg) ratio. In addition we analysed the rock and mineral spectra, and extracted chlorite characteristic spectral parameters. The relationship between the spectra feature parameters and the main crystal chemical parameters in chlorite was analyzed. The study indicated that the diagnostic spectral wavelength of chlorites moved to long wavelength. The results have important guiding significance for identifying the alteration and rock forming mineral species, composition and structure characteristics by usinghyperspectral remote sensing technology.
RESUMEN
Estimating minerals abundance from reflectance spectra is one of the fundamental goals of remote sensing lunar exploration, and the main difficulties are the complicated mixing law of minerals spectrum and spectral features being sensitive to several kinds of factors such as topography, particle size and roughness etc. A method based on spectral unmixing was put forward and tested in the present paper. Before spectra are unmixed the spectral continuum is removed for clarifying and strengthening spectral features. The absorption features and reflectance features (the upward curving parts of spectra between absorption features) are integrated for unmixing to improve the unmixing performance. The Hapke model was used to correct unmixing error due to nonlinear mixing of minerals spectra. Forty three mixed spectra of olivine, clinopyroxene, hypersthene and plagioclase were used to validate the above method. The four minerals abundance was estimated under the conditions of being unaware of endmember spectra used to mix, granularity and chemical composition of minerals. Residual error, abundance error and correlation coefficient between retrieved and true abundance were 5.0 Vol%, 14.4 Vol% and 0.92 respectively. The method and result of this paper could be referred in the lunar minerals mapping of imaging spectrometer data such as M3.