A study on the electromagnetic propagation in various\ud
models of the Martian subsurface is performed with a relevance\ud
to ground penetrating radar (GPR) operating onboard\ud
rover missions. Measurements of the electromagnetic properties of\ud
Mars soil simulants are obtained; on this basis, the attenuation\ud
features of the GPR signals are estimated, including both electric\ud
and magnetic losses. The effect on propagation of inhomogeneities\ud
inside the soil is also taken into account by means of a specific\ud
model with randomly distributed scatterers. The GPR performance\ud
in terms of resolution and maximum penetration depth\ud
is evaluated in the considered scenarios for different operating\ud
frequencies, thus providing a basic information for the design of\ud
systems for future subsurface sounding investigations on Mars
An algorithm for pre-operational high resolution soil moisture mapping using Synthetic Aperture Radar (SAR) data is presented. It has been conceived to be inserted in the operational weather alert system of the Italian Department of Civil Protection. The Maximum A Posteriori (MAP) probability criterion is applied to retrieve soil moisture by inverting a forward backscattering model, and ancillary data such as optical images and land cover maps are also used to identify areas in which the retrieval can be carried out. The well-established semiempirical water cloud model is adopted to correct for the effect of vegetation on SAR data. In anticipation of the use of the algorithm in an operational system, in which the SAR-derived high resolution soil moisture product can be assimilated within weather prediction models or hydrological ones, an uncertainty index is associated to each estimate. The algorithm has been tested on a dataset consisting of ground data gathered for seven years (2003-2010) on an agricultural test site in Northern Italy and radar data provided by the C-band ENVISAT/ASAR instrument. A comparison, performed at field scale, between estimated and in situ soil moisture data has shown that, by discarding the estimates with the largest uncertainty, the correlation coefficient can exceed 0.80 and the root mean square estimation error is less than 0.05 m(3)/m(3). Moreover, the uncertainty index has turned out to be fairly correlated to the actual estimation error
The sensitivity of bistatic scattering coefficient sigma degrees to soil moisture content (SMC) and surface roughness was investigated by means of model simulations of the incoherent scattered fields performed with the advanced integral equation model (AIEM) and the second order small perturbation model (SPM). The study was performed by simulating scattering on the whole upper half space, for different values of incident angles. The achieved results, represented as maps of sigma degrees as a function of azimuth and zenith angles, were evaluated by means of a quality index which takes into consideration the effect of roughness on SMC measurement. The sensitivity analysis has pointed out that for measuring SMC a bistatic observation, by itself or combined with the monostatic one, can make appreciable improvements with respect to classical monostatic radar. Appendix A contains the AIEM formulas corrected for several typographical errors present in the specific literature
For more than two decades, radar altimetry missions have provided continuous elevation estimates of the Greenland Ice Sheet (GrIS). Here, we propose a method for using such data to estimate ice sheet-wide surface elevation changes (SEC). The final dataset will be based on observations acquired with the European Space Agency's Envisat, ERS-1 and -2, CryoSat-2, and, in the longer term, Sentinel-3 satellites. In order to find the best-performing method, an inter-comparison exercise has been carried out in which the scientific community was asked to provide their best SEC estimate as well as a feedback sheet describing the applied method. Due to the hitherto few radarbased SEC analyses as well as the higher accuracy of laser data, the participants were asked to use either Envisat radar or ICESat (Ice, Cloud, and land Elevation Satellite) laser altimetry over the Jakobshavn Isbrae drainage basin. The submissions were validated against airborne laser-scanner data, and inter-comparisons were carried out to analyze the potential in the applied methods and whether the two altimeters were capable of resolving the same signal. The analyses found great potential in the applied repeat-track and cross-over techniques, and, for the first time over Greenland, that repeat-track analyses from radar altimetry agreed well with laser data. Since topography-related errors can be neglected in cross-over analyses, it is expected that the most accurate, ice sheet-wide SEC estimates are obtained by combining the cross- * Corresponding author. E-mail:JFL@space.dtu.dk 1 November 7, 2014 International Journal of Remote Sensing tRES˙JFL˙subm over and repeat-track techniques. It is thus possible to exploit the high accuracy of the former and the large spatial data coverage of the latter. Based on CryoSat's different operation modes, and the increased spatial and temporal data coverage, this shows good potential for a future inclusion of CryoSat-2 and Sentinel-3 data to continuously obtain accurate SEC estimates both in the interior and margin ice sheet.
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