[Previous] | [Session 26] | [Next]
D. R. Klassen (Rowan University)
Previous studies [1--3] have shown that principal components analysis (PCA) can be used on near-infrared (NIR) spectral images in the 1.5--4.1\,\mum spectral region to detect Martian ices, on the ground and as clouds, with great reliability. This is made possible because spectral differences between the ice and the surrounding surface contributes significantly to the spectral variance. It also helps that the water ice clouds make up a significant portion of the visible scene during the northern summer.
In this work, the technique is applied to images gathered at the NASA Infrared Telescope Facility using NSFCAM in the same spectral range, but during the recent southern summer oppositions (2001 and 2003). In this season, ice cloud cover is primarily restricted to orographic features---cap clouds over the major volcanoes. It will be shown that PCA still picks out the cold, volatile covered regions since the spectral features are strong enough to contribute significantly to the spectral variance despite being more geographically restricted. What is more, there appears to be a separation in the principal component relating to cold volatiles that distinguishes between the, presumably, water ice clouds and the CO2 ice in the residual south polar cap.
\textbf{References} [1] Klassen, D. R., \emph{et al.} (1999) Icarus, 138, 36. [2] Klassen, D. R. and Bell III, J. F. (2001) BAAS, 33, 1069. [3] Klassen, D. R. and Bell III, J. F. (2003) BAAS, 35, 936. \textbf{Acknowledgements} This work is supported by a grant from the NASA Mars Data Analysis, and NSF-RUI programs.
The author(s) of this abstract have provided an email address for comments about the abstract: klassen@rowan.edu
[Previous] | [Session 26] | [Next]
Bulletin of the American Astronomical Society, 36 #4
© 2004. The American Astronomical Soceity.