Analysis Of Selected VIMS And RADAR Data Over The Surface Of Titan Through Multivariate Statistical Methods

Details Analysis Of Selected VIMS And RADAR Data Over The Surface Of Titan Through Multivariate Statistical Methods Analysis Of Selected VIMS And RADAR Data Over The Surface Of Titan Through Multivariate Statistical Methods

Sep 2008

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008dps....40.3115t&link_type=abstract

American Astronomical Society, DPS meeting #40, #31.15; Bulletin of the American Astronomical Society, Vol. 40, p.449

Astronomy and Astrophysics

Astronomy

Scientific paper

In this work we have searched through Cassini/VIMS hyperspectral cubes, selecting those data which have convenient viewing geometry and which overlap with Cassini/RADAR footprints having comparable ground resolution, in order to properly look for correlations between the infrared and microwave ranges explored by the two instruments.
In RADAR data we have considered two geophysical quantities: the normalized backscatter cross-section obtained from the scatterometer measurement, corrected for the incidence angle, and the brightness temperature determined from the radiometer measurement, as found in publicly available data products.
In VIMS data, combining spatial and spectral information, we have selected some atmospheric windows in the spectral range between 2 and 5 μm, providing the best optical depth to measure surface reflectance.
The two RADAR parameters are combined with the VIMS data, with estimated errors, to produce an aggregate data set, that we process using multivariate classification methods to identify homogeneous taxonomic units in the multivariate space of the samples. The use of data sets from different instruments onboard the Cassini spacecraft is a necessary step towards understanding the nature and history of Titan, since correlations between different physical processes can be highlighted.
A first analysis has been done with the G-mode method, which has been successfully used in the past for the classification of such diverse data sets as lunar rock samples, asteroids and planetary surfaces. Due to the large number of Titan data, the classification work is still ongoing; nevertheless the obtained results are generally in agreement with previous works aimed both to the analysis of the scatterometry data through physical models and to the correlation between SAR and radiometry data at a high resolution scale.
These evidences, evaluated for the first time through a multivariate statistical method, can provide constraints on the geophysical models under development for the surface of Titan.

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