Mathematics – Logic
Scientific paper
Dec 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004spie.5660..151g&link_type=abstract
Instruments, Science, and Methods for Geospace and Planetary Remote Sensing. Edited by Nardell, Carl A.; Lucey, Paul G.; Yee, J
Mathematics
Logic
Scientific paper
The ability to measure TiO2 remotely is important for mapping the composition lunar basalt flows globally, and for placing lunar samples into a regional and global geologic context. Comparing Clementine UVVIS-ratio (415/750 nm) with Lunar Prospector derived TiO2 data, however, yields a less than ideal correlation, which would suggest that either the UVVIS ratio has poor predictive capabilities with respect to TiO2 composition or poor accuracy of the Lunar Prospector TiO2 data. Established uncertainties of the Clementine UVVIS data are approximately 1%, while the reported relative errors for Lunar Prospector neutron spectrometer data are on the order of 5%. Thus, we investigate the possibility of whether the greater uncertainty of the Lunar Prospector neutron data could cause the poor correlation between the two data sets. The sensitivity of the TiO2-UVVIS correlation to data accuracy was measured by adding randomly-distributed noise to the Clementine UVVIS data, and then comparing this modified Clementine data with the "noiseless" Clementine data. The comparison was then evaluated for the level of noise needed to produce a similar amount of scatter observed in the Lunar Prospector TiO2 and Clementine UVVIS-ratio trend. The results of this study indicate that Lunar Prospector would have to possess significantly more than 5% uncertainty to match the observed poor correlation between Lunar Prospector and Clementine data sets. On this basis, we concluded that algorithms that depend solely upon correlations between UV and visible spectral parameters and TiO2 concentration have inherently poor predicting power.
Gillis Jeffery J.
Lucey Paul G.
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