Automatic Detection and Characterization of Subsurface Features from Mars Radar Sounder Data

MARSIS and SHARAD are currently orbiting Mars in an attempt to explore structural and volatile elements in its subsurface. The data returned from these two experiments are complementary in their nature for providing different penetration capabilities and vertical resolutions that is crucial to constrain the ambiguities on the subsurface structural and geophysical properties. To this day, both radars have acquired a substantial large volume of data that are yet to be quantitatively analyzed with more accurate radar inversion algorithms. Manual investigation of the radargrams is a time consuming task that is often dependent on user visual ability to distinguish subsurface reflectors. Such process induces a substantial ambiguity in data analysis from user to user, limits the amount of data to be explored and reduces efficiency of fusion studies to compile MARSIS and SHARAD data in a metric process. To address this deficiency, we started the development of automated techniques for the extraction of subsurface information from the radar sounding data. Such methods will greatly improve the ability to perform scientific analysis on larger scale areas using the two data sets from MARSIS and SHARAD simultaneously [Ferro and Bruzzone, 2009]. Our automated data analysis chain has been preliminarily applied only to SHARAD data for the statistical characterization of the radargrams and the automatic detection of linear subsurface features [Ferro and Bruzzone, 2010]. Our current development has been extended for the integration of both SHARAD and MARSIS data. We identified two targets of interest to test and validate our automated tools to explore subsurface features: (1) The North Polar Layer Deposits, and (2) Elysium Planitia. On the NPLD, the technique was able to extract the position and the extension of the returns coming from basal unit from SHARAD radargrams, both in range and azimuth. Therefore, it was possible to map the depth and thickness of the icy polar cap. The proposed technique has thus substantial potential in supporting subsurface reflection assessment over widespread geologic areas. In particular it could highlight features which are not detectable from the analysis of single tracks separately, such as buried impact craters or basins. We will finally present a joint analysis conducted over Elysium Planitia where we combined the results obtained by the automatic detection of subsurface linear features from SHARAD data with the estimation of subsurface losses from MARSIS data. The latter has been performed by means of an automatic procedure which allows the user to calculate the losses over a given area using the time decay method.