Landfast First-Year Snow-Covered Sea Ice Reconstruction via Electromagnetic Inversion

The inversion of the monostatic normalized radar cross section (NRCS) data collected by an on-site C-band scatterometer and also RADARSAT-2 satellite are investigated to reconstruct some parameters of interest associated with landfast snow-covered sea ice in Cambridge Bay, Nunavut, Canada. The parameters of interest are temperature, density, salinity, and snow grain size. To this end, this remote sensing problem is cast as an inverse scattering problem in which a data misfit cost functional is to be minimized using a differential evolution algorithm. This minimization requires repetitive calls to an appropriate electromagnetic forward solver. The utilized electromagnetic forward solver attempts to model both surface and volume scattering components associated with the irradiated rough multilayered medium under investigation. The reconstruction results demonstrate the ability of this inversion algorithm to retrieve the parameters of interest with reasonable accuracy. In particular, the best performance of the inversion algorithm occurs when both the scatterometer and satellite NRCS data are simultaneously used in the inversion process.