Towards a Pol-InSAR Firn Density Retrieval

Kurzfassung

Polarimetric and (multi-baseline) interferometric SAR techniques are promising tools to investigate the subsurface properties of glaciers and ice sheets, due to the signal penetration of up to several tens of meters into dry snow, firn, and ice. Two different lines of research were addressed in recent years. The first is based on PolSAR, which provides not only information about the scattering mechanisms, but also has the uniqueness of being sensitive to anisotropic signal propagation in non-scattering layers of snow and firn. The second line of research is related to the use of Pol-InSAR and TomoSAR to retrieve the 3D location of scatterers within the subsurface. So far, the different SAR techniques were mainly assessed separately. In the field of PolSAR modeling efforts have been dedicated to establish a link between the co-polarization HH-VV phase difference (CPD) and the structural properties of firn [1]. CPDs have then been interpreted as the result of propagation effects due to the dielectric anisotropy of the firn volume. This modeling approach establishes a relationship between the measured CPD and firn density, firn anisotropy and the vertical backscattering distribution in the subsurface of the glacier or ice sheet. By assuming bulk values for density and anisotropy and employing a constant signal extinction for the vertical backscattering function, i.e. a uniform volume, a first attempt to retrieve firn thickness from PolSAR data was presented [1]. In the fields of Pol-InSAR and TomoSAR for the investigation of the subsurface scattering structure of glaciers and ice sheets, recent studies were concerned with the estimation of the vertical backscatter distribution, either model-based or through tomographic imaging techniques. The complexity of (Pol-)InSAR models for the retrieval of subsurface structure information is mainly limited by the available observation space. Thus, constant signal extinction volumes [2], with additional Dirac deltas to represent refrozen melt layers [3] and variable extinction volumes [4] have been modelled and used to retrieve information about the subsurface. With TomoSAR, the imaging of subsurface features in glaciers [5], and ice sheets [4][6][7] was demonstrated and the effect of subsurface layers, different ice types, firn bodies, crevasses, and bed rock was recognized in the tomograms. Those studies on PolSAR, Pol-InSAR and TomoSAR techniques made promising steps towards a subsurface structure information retrieval on glaciers and ice sheets, but the direct relationship to geophysical parameters, which are useful for the glaciological community, is only limited. The most promising way to achieve this goal is the combination of PolSAR and Pol-InSAR/TomoSAR techniques in order to exploit the synergies between the individual methods and by integrating the models and algorithms into one common framework. A first experiment in this direction was the integration of TomoSAR vertical scattering profiles into the PolSAR firn anisotropy model [8]. This allowed the inversion of the firn density from experimental airborne F-SAR data over Greenland, which would be a promising geophysical information product. However, this experiment enabled only the inversion of a single bulk density value for the entire penetration depth and was based on hundreds of samples of CPD measurements and TomoSAR profiles across a wide range of incidence angles, which is of limited applicability. Therefore, this study will continue this investigation, assessing to which degree an inversion is possible on reduced and more feasible observation spaces. Open questions are, which number and range of incidence angles as well as which and how many baselines are required, and whether depth-varying densities could be retrieved. The results should give an indication if such an approach might be feasible with future spaceborne SAR systems. [1] G. Parrella, I. Hajnsek, and K. P. Papathanassiou, “Retrieval of Firn Thickness by Means of Polarisation Phase Differences in L-Band SAR Data,” Remote Sensing, vol. 13, no. 21, p. 4448, Nov. 2021, doi: 10.3390/rs13214448. [2] E. W. Hoen and H. Zebker, “Penetration depths inferred from interferometric volume decorrelation observed over the Greenland ice sheet,” IEEE Transactions on Geoscience and Remote Sensing, vol. 38, no. 6, pp. 2571–2583, 2000. [3] G. Fischer, K. P. Papathanassiou and I. Hajnsek, "Modeling Multifrequency Pol-InSAR Data from the Percolation Zone of the Greenland Ice Sheet," IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 4, pp. 1963-1976, 2019. [4] G. Fischer, M. Jäger, K. P. Papathanassiou and I. Hajnsek, "Modeling the Vertical Backscattering Distribution in the Percolation Zone of the Greenland Ice Sheet with SAR Tomography," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 11, pp. 4389-4405, 2019. [5] S. Tebaldini, T. Nagler, H. Rott, and A. Heilig, “Imaging the Internal Structure of an Alpine Glacier via L-Band Airborne SAR Tomography,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 12, pp. 7197–7209, 2016. [6] F. Banda, J. Dall, and S. Tebaldini, “Single and Multipolarimetric P-Band SAR Tomography of Subsurface Ice Structure,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 5, pp. 2832–2845, 2016. [7] M. Pardini, G. Parrella, G. Fischer, and K. Papathanassiou, “A Multi-Frequency SAR Tomographic Characterization of Sub-Surface Ice Volumes,” in Proceedings of EUSAR, Hamburg, Germany, 2016. [8] G. Fischer, K. Papathanassiou, I. Hajnsek, and G. Parrella, “Combining PolSAR, Pol-InSAR and TomoSAR for Snow and Ice Subsurface Characterization,” in Proceedings of the ESA POLinSAR Workshop, Online, Apr. 2021.