Mathematics – Logic
Scientific paper
Jan 1998
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1998nvmi.conf...53l&link_type=abstract
Workshop on New Views of the Moon: Integrated Remotely Sensed, Geophysical, and Sample Datasets, p. 53
Mathematics
Logic
Lunar Soil, Lunar Surface, Mineralogy, Reflectance, Surface Properties, Geochemistry, Lunar Geology, Selenology, Lunar Composition, Absorption Spectra, Ilmenite, Spectroscopy
Scientific paper
The methods developed recently for derivation of Fe and Ti from multispectral imaging of the Moon are empirical, but were guided in their development by a qualitative model of the lunar surface spectral properties enunciated by Rava and Hapke. Their development also critically depended on a dataset for lunar soils where both reflectance spectra and the elemental abundance methods have known (at least upper) limits on their accuracy and precision by comparing abundance measurements of the soils used to develop and test these techniques. Some of the uncertainty observed in the deviations between measured and predicted element concentrations are likely due to shortcomings in the assumptions in the methods. These include that particle size or size distribution is constant or a smooth function of composition, that Ti is primarily partitioned into ilmenite and that ilmenite, is the sole opaque, or that the ratio of ilmenite to other opaques is constant or a smooth function of TiO2 content, and that the specific mineral in which ferrous Fe resides is unimportant. In the list above the phrase "smooth function of composition" is often repeated. Because the methods are empirical, that is, they are calibrated against known compositions, certain types of these assumption violations do not give rise to errors. The types are those where important parameters such as grain size are highly correlated with composition. Any parameter that ordinarily might be a profound source of error will be compensated if its variations are primarily correlated with the relevant elemental concentration. Limitations in accuracy and precision due to mineralogic variations have not been sufficiently explored. The major mafic minerals all possess absorption bands near I pm and to first order they have similar strengths at the same concentration of Fe, but this has not been quantified. Any differences in band strengths at constant FeO among the different minerals will give rise to mineralogy-dependent systematic errors. We have made preliminary measurements that suggested that this effect is minor, but more work is necessary. Also, mineralogy can affect the distribution of Fe. Do two soils with identical FeO values but greatly different Mg numbers give rise to the same FeO content predicted from spectra? Again,we have made preliminary measurements that suggested this effect is minor, but more work in this area is necessary. These dependencies will be presented at the workshop.
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