Partial Least Squares Modeling of Lunar Surface FeO Content with Clementine Ultraviolet-Visible Images - Planetary Exploration and Science: Recent Results and Advances - page 4

and perform better than PCA in the estimation of lunar chemical and mineral
abundances. However, Li didn't apply his result to lunar remotely sensed images.
Our PLS-derived iron model is developed with intent to explore the potential of
the UVVIS imaging dataset. During the modeling, we find it is easy to reach a
good regression relationship (high correlation efficient (R 2 ) value) between spectra
parameters and iron contents, while maturity suppressing is more difficult to attain.
We have tested many different variables in PLS modeling to find the most applicable
one for Clementine UVVIS images and compare our results with previous studies
to evaluate the robustness of the PLS model.

1.2 Data

The lunar remote sensing images used in this study are from Clementine UVVIS
Digital Image Model (DIM) published by US Geological Survey (USGS) Astrogeol-
ogy Team at Flagstaff, Arizona (NASA PDS Geosciences Node). The DIM has five
bands with a nominal ground resolution at 100 m/pixel, and the center wavelengths
(spectra resolutions) of the five filters are A, 415 nm (40 nm); B, 750 nm (10 nm);
C, 900 nm (20 nm); D, 950 nm (30 nm); and E, 1,000 nm (30 nm) (Eliason et al.
1999 ). This dataset is archived in the NASA Planetary Data System, and each image
has undergone radiometric and geometric correction, spectral registration, and
photometric normalization by Integrated Software for Imagers and Spectrometers
(ISIS) processing system.
The PLS modeling data points include those extracted from Apollo and Luna
sampling stations (from Wilcox et al. ( 2005 ), Table 2) and supplementary data from
farside highlands and optically fresh (immature) areas (shown in Table 1.1 ). From
our experiments, the statistical prediction of chemical abundance rely significantly
on the input variables, i.e., an obvious deviation of iron abundance would appear
when the modeling didn't include data points from farside highland and immature
areas. Note that the iron abundances of supplementary data in Table 1.1 were
calculated with Lucey's ( 2000 ) parameters.

Tabl e 1. 1 Iron abundance and reflectance values of supplementary data from Clementine UVVIS

Clementine spectra

Sites 415 nm 750 nm 900 nm 950 nm 1,000 nm FeO (wt%)

Farside-1 0.1196 0.2022 0.2178 0.2250 0.2302 2.3

Farside-2 0.1195 0.2032 0.2183 0.2271 0.2336 1.7

Farside-3 0.1330 0.2271 0.2372 0.2447 0.2546 3.8

Fresh-1 0.0794 0.1265 0.1140 0.1108 0.1111 17.2

Fresh-2 0.0767 0.1229 0.11155 0.1088 0.1103 17.4

Fresh-3 0.0811 0.1353 0.1202 0.1174 0.1203 16.8