Principle Components Analysis of Mars at the 2003 Opposition

Astronomy and Astrophysics – Astronomy

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Scientific paper

The perihelic opposition of Mars in 2003 allowed us to gather very high spatial resolution spectral images in the 1.5--4.1 μ m region. As has been shown in earlier work [1--3] this spectral region can be used to distinguish both H2O and CO2 clouds. Band ratio maps of NIR spectral features however can be confused by surface mineralogy features. Thus the use of principle components analysis (PCA).
Our previous PCA work on Mars spectral images [2, 4, 5] has shown that the cold, ice clouds can be distinguished from the warmer surface. This is possible because PCA looks at spectral variance across the spectrum as a whole instead of single spectral features. It also helps that the water ice clouds make up a significant portion of the visible scene during the northern summer.
In the 2003 opposition, the northern hemisphere is in its winter season and cloud activity is expected to be limited to high topographic regions and possibly near the terminator. Since water ice makes up a much smaller fraction of the visible scene, we expect that this may affect the exact principle components derived from the analysis, and allow for a far clearer analysis of the surface itself. In this way we expect to be able to derive a ``surface'' component spectrum, in much the same manner as Bandefield \textit{et al.} [6], to use in spectral mixture modeling.
We present here the PCA results of the 2003 opposition spectral images of Mars in the near-infrared and discuss their implications on our ongoing cloud modeling program.
\textbf{References} [1] Bell III, J. F. and Crisp, D. (1993) Icarus, 104, 2. [2] Klassen, D. R., et al. (1999) Icarus, 138, 36. [3] Klassen, D. R. and Bell III, J. F. (2003) Icarus, 163, 66. [4] Klassen, D. R. and Bell III, J. F. (2001) BAAS, 33, 1069. [5] Klassen, D. R. and Bell III, J. F. (2003) BAAS, 35, 936. [6] Bandfield, J. L., Christensen, P. R., and Smith, M. D. (2000) JGR, 105, 9573.
\textbf{Acknowledgements} This work is supported by a grant from the NASA Mars Data Analysis, and NSF-RUI programs.

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