Physics
Scientific paper
Dec 2007
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007agufm.p22b..02t&link_type=abstract
American Geophysical Union, Fall Meeting 2007, abstract #P22B-02
Physics
5405 Atmospheres (0343, 1060), 5464 Remote Sensing, 5470 Surface Materials And Properties, 5494 Instruments And Techniques, 6281 Titan
Scientific paper
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.\newline 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.\newline In VIMS data, we have selected the infrared wavelengths in the methane windows, which provide the best optical depth to measure surface reflectance.\newline 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.\newline 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. This method can be used without any a priori knowledge of the taxonomic structure of the observations, which is in fact provided by the classification. Furthermore, independence of variables and samples is not required, although the relationship between variables and samples needs to be known.\newline Through this classification we search for information which would not be obtained from the individual data sets alone, to gain insight about the nature and physical structure of the surface.\newline This research is supported by the Italian Space Agency (ASI).
Adriani Alberto
Capaccioni Fabrizio
Cassini RADAR Team
Cassini Science Team
Cerroni Pricilla
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