Antarctic snow-covered sea ice topography derivation from TanDEM-X using polarimetric SAR interferometry

Abstract

Abstract. Single-pass interferometric synthetic aperture radar (InSAR) enables the possibility for sea ice topographic retrieval despite the inherent dynamics of sea ice. InSAR digital elevation models (DEMs) are measuring the radar scattering center height. The height bias induced by the penetration of electromagnetic waves into snow and ice leads to inaccuracies of the InSAR DEM, especially for thick and deformed sea ice with snow cover. In this study, an elevation difference between the satellite-measured InSAR DEM and the airborne-measured optical DEM is observed from a coordinated campaign over the western Weddell Sea in Antarctica. The objective is to correct the penetration bias and generate a precise sea ice topographic map from the single-pass InSAR data. With the potential of retrieving sea ice geophysical information by the polarimetric-interferometry (Pol-InSAR) technique, a two-layer-plus-volume model is proposed to represent the sea ice vertical structure and its scattering mechanisms. Furthermore, a simplified version of the model is derived, to allow its inversion with limited a priori knowledge, which is then applied to a topographic retrieval scheme. The experiments are performed across four polarizations: HH, VV, Pauli 1 (HH + VV), and Pauli 2 (HH − VV). The model-retrieved performance is validated with the optically derived DEM of the sea ice topography, showing an excellent performance with root-mean-square error as low as 0.26 m in Pauli-1 (HH + VV) polarization.

Snow Penetration Depth Inversion in Tibetan Plateau Based on Coherence Scattering Model with X-band Data

“…are known. The effect of the dielectric constant on the penetration depth can be compensated by the change in the incidence angle, so the effect of the change in the dielectric constant of snow on the penetration depth is negligible (Huang et al 2021), so 𝜀 = 1.763 is taken (Matzler 1996). The final H aVol calculations are shown in Figure 7.…”

Synthetic Aperture Radar (SAR) for Ocean: A Review

“…There are many different characteristics associated with each of these frequencies and polarizations that make them more suitable and informative for a specific application [210], [211]. • Due to the higher wavelength of the microwave signals, SAR can penetrate into shallow water, snow, ground [212], [213]. Depth of the penetration depends on both the sensor characteristics (e.g., incident angle, and imaging frequency) and physical characteristics of the target (e.g., moisture, and turbidity) [212], [213].…”

“…• Due to the higher wavelength of the microwave signals, SAR can penetrate into shallow water, snow, ground [212], [213]. Depth of the penetration depends on both the sensor characteristics (e.g., incident angle, and imaging frequency) and physical characteristics of the target (e.g., moisture, and turbidity) [212], [213]. • SAR images are capable of providing a wide range of information about the imaging surface or object, including physical (e.g., dielectric constant, surface roughness, etc.…”

An On-Site InSAR Terrain Imaging Method with Unmanned Aerial Vehicles

“…For example, the Antarctic ice sheet (AIS) is covered with rifts and crevasses off the map, endangering the exploration personnel [38,39]. Satellite-borne sensors cannot provide updated images and information for on-site tasks [38,40], but can be complemented with the InSAR images acquired with UAVs. Typical satellite-borne platforms take days to revisit the same area, with a baseline of a few hundred meters, while UAV-borne platforms can revisit the same area immediately after the previous flight, with a baseline of a few meters.…”