Dry Snow Parameter Retrieval With Ground-Based Single-Pass Synthetic Aperture Radar Interferometry

2022 
In this article, we investigate the potential of using single-pass InSAR model-based approaches to retrieve dry snow parameters. Two InSAR scattering models of dry snow are considered: the dense-medium random volume over ground (RVoG) model and the simple variant of the full penetration (FP) model. A quasi-crystalline approximation (QCA)-based extinction analysis confirms the negligible extinction dependence of the InSAR observables at L/C/X-band for fresh dry snow. The FP models the low-frequency (L/C/X-band) InSAR phase as a single constraint of snow depth and density, which can be supplemented by an extra observation (e.g., InSAR coherence or in situ depth/density). The single-pass InSAR models and inversion approaches were validated using X-band InSAR data collected from a tower-based three-frequency (X/Ku-low/Ku-high) fully polarimetric TomoSAR system, where a multi-frequency polarimetric InSAR analysis and ground-to-volume ratio-based snow condition analysis were conducted. We also analyzed the sensitivity and error propagation of the single-pass InSAR phase and coherence in measuring dry snow depth/density. It was found that the X-band HH-pol FP-modeled single-pass InSAR phase along with RVoG-modeled coherence or in situ depth is capable of measuring snow water equivalent (SWE) with a 23–26 mm uncertainty (13–15%) and a 20–26 mm bias (12–15%) for dry snow SWE of 0.2 m, and with an optimal perpendicular baseline on the order of a tenth of the snow depth (0.8 m) at our test site. This single-pass InSAR approach with the FP model is potentially useful and thus needs further investigation for large-scale dry snow retrieval with a wide range of snow conditions using ground-based/airborne/spaceborne low-frequency (L/C/X-band) InSAR observations.
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