Open AccessRadiative transfer modeling of near‐infrared reflectance of lunar highland and mare soils
Author(s) -
Cahill J. T. S.,
Lucey P. G.,
StockstillCahill K. R.,
Hawke B. R.
Publication year - 2010
Publication title -
journal of geophysical research: planets
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2009je003500
Subject(s) - hyperspectral imaging , radiative transfer , atmospheric radiative transfer codes , soil water , spectral resolution , remote sensing , mineralogy , spectral line , geology , spectral slope , environmental science , soil science , optics , physics , astronomy
With near‐infrared hyperspectral data sets returned from KAGUYA/SELENE and Chandrayaan‐1's Moon Mineralogic Mapper (M 3 ), accurate evaluation and interpretation of lunar data sets with higher spectral resolution has never been more critical. Here we test a new radiative transfer spectral modeling algorithm to determine composition from hyperspectral reflectance spectra of lunar soils. Data for 19 lunar mare and highland soil samples previously characterized by the Lunar Soil Characterization Consortium are used for validation. Spectral fits are made using a goodness of fit metric considering spectral shape, spectral contrast, spectral slope, and iron abundance. High precision fits are achieved for nearly every soil with this algorithm. Using a plot of spectral shape relative to the ratio Mg′ (i.e., molar (Mg/(Mg + Fe)) × 100) determines the winning model and composition. Mg′ is determined with an average difference of ∼11–15 and ∼3–8 units before and after a correction is applied, respectively. Mineralogy is determined with an average difference of ∼5–15 vol% depending upon the mineral constituent.