Computer Science – Performance
Scientific paper
Sep 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011jgre..11609001l&link_type=abstract
Journal of Geophysical Research, Volume 116, Issue E9, CiteID E09001
Computer Science
Performance
Hydrology: Rocks: Physical Properties, Atmospheric Processes: Remote Sensing (4337), Mineralogy And Petrology: Planetary Mineralogy And Petrology (5410), Natural Hazards: Space Weather (2101, 2788, 7900)
Scientific paper
The main objective of this work is to quantify lunar surface minerals (agglutinate, clinopyroxene, orthopyroxene, plagioclase, olivine, ilmenite, and volcanic glass), particle sizes, and the abundance of submicroscopic metallic Fe (SMFe) from the Lunar Soil Characterization Consortium (LSCC) data set with Hapke's radiative transfer theory. The mode is implemented for both forward and inverse modeling. We implement Hapke's radiative transfer theory in the inverse mode in which, instead of commonly used look-up tables, Newton's method and least squares are jointly used to solve nonlinear questions. Although the effects of temperature and surface roughness are incorporated into the implementation to improve the model performance for application of lunar spacecraft data, these effects cannot be extensively addressed in the current work because of the use of lab-measured reflectance data. Our forward radiative transfer model results show that the correlation coefficients between modeled and measured spectra are over 0.99. For the inverse model, the distribution of the particle sizes is all within their measured range. The range of modeled SMFe for highland samples is 0.01%-0.5%, and for mare samples it is 0.03%-1%. The linear trend between SMFe and ferromagnetic resonance (Is) for all the LSCC samples is consistent with laboratory measurements. For quantifying lunar mineral abundances, the results show that the R squared for the training samples (Is/FeO ≤ 65) are over 0.65 with plagioclase having highest correlation (0.94) and pyroxene having the lowest correlation (0.68). In future work, the model needs to be improved for handling more mature lunar soil samples.
Li Lin
Li Shuai
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