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| Content Provider | Springer Nature Link |
|---|---|
| Author | Li, Lin |
| Copyright Year | 2011 |
| Abstract | Partial least squares (PLS) regression was applied to the Lunar Soil Characterization Consortium (LSCC) dataset for spectral estimation of TiO$_{2}$. The LSCC dataset was split into a number of subsets including the low-Ti, high-Ti, total mare soils, total highland, Apollo 16, and Apollo 14 soils to investigate the effects of interfering minerals and nonlinearity on the PLS performance. The PLS weight loading vectors were analyzed through stepwise multiple regression analysis (SMRA) to identify mineral species driving and interfering the PLS performance. PLS exhibits high performance for estimating TiO$_{2}$ for the LSCC low-Ti and high-Ti mare samples and both groups analyzed together. The results suggest that while the dominant TiO$_{2}$-bearing minerals are few, additional PLS factors are required to compensate the effects on the important PLS factors of minerals that are not highly corrected to TiO$_{2}$, to accommodate nonlinear relationships between reflectance and TiO$_{2}$, and to correct inconsistent mineral-TiO$_{2}$ correlations between the high-Ti and low-Ti mare samples. Analysis of the LSCC highland soil samples indicates that the Apollo 16 soils are responsible for the large errors of TiO$_{2}$ estimates when the soils are modeled with other subgroups. For the LSCC Apollo 16 samples, the dominant spectral effects of plagioclase over other dark minerals are primarily responsible for large errors of estimated TiO$_{2}$. For the Apollo 14 soils, more accurate estimation for TiO$_{2}$ is attributed to the positive correlation between a major TiO$_{2}$-bearing component and TiO$_{2}$, explaining why the Apollo 14 soils follow the regression trend when analyzed with other soils groups. |
| Starting Page | 549 |
| Ending Page | 565 |
| Page Count | 17 |
| File Format | |
| ISSN | 1674487X |
| Journal | Journal of Earth Science |
| Volume Number | 22 |
| Issue Number | 5 |
| e-ISSN | 1867111X |
| Language | English |
| Publisher | China University of Geosciences |
| Publisher Date | 2011-09-30 |
| Publisher Place | China University of Geosciences |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | lunar soils LSCC dataset TiO$_{2}$ abundance partial least squares stepwise multiple regression Geochemistry Earth Sciences Applied Earth Sciences Geology |
| Content Type | Text |
| Resource Type | Article |
| Subject | Earth and Planetary Sciences |
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