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

Abstract

In this paper, 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 RVoG model and the simple variant of 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 Xband 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-tovolume 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 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 lowfrequency (L/C/X-band) InSAR observations.

Polarimetric Analysis of Biseasonal Monostatic and Bistatic Radar Observations of a Glacier Accumulation Zone at Ku-Band

“…The active measurements spanning from 9.15 GHz to 17.9 GHz were performed with the SnowScat instrument [32]. • As part of the NASA SnowEx project, the SRT3 fullpolarimetric radar performed X-and Ku-band observations of snow cover [71] and the observations were used for parameter retrieval [72], [73].…”

A Novel Method for Snow Depth Retrieval Using Improved Dense Medium RVoG Model

“…Interferometric SAR (InSAR) is more responsive to the height structure of the target and is one of the promising methods for retrieving the target height introduced in recent years [17]. According to the different SAR data acquisition modes, InSAR can be classified into two types: single-pass InSAR and repeat-pass InSAR [18]. Single-pass InSAR is almost free from temporal decorrelation and atmospheric delay effects, and the phases from the two antennae can be used directly to indicate the wet snow depth of the top layer [19].…”

“…Single-pass InSAR is almost free from temporal decorrelation and atmospheric delay effects, and the phases from the two antennae can be used directly to indicate the wet snow depth of the top layer [19]. However, for dry snow mixed with ground/volume scattering, snow depth retrieval based on single-pass InSAR needs to be combined with the InSAR model and consider the applicability of the spatial baseline to the model, which increases the complexity of the snow depth retrieval method for dry snow from the single-pass InSAR data [18]. The repeated-pass InSAR uses the phase of SAR data before and after snowfall to retrieve snow depth, which may suffer from temporal decorrelation, but the repeated-pass InSAR can obtain the phase difference information from before and after snowfall easily, which is the wider application in dry snow depth retrieval [18].…”

“…However, for dry snow mixed with ground/volume scattering, snow depth retrieval based on single-pass InSAR needs to be combined with the InSAR model and consider the applicability of the spatial baseline to the model, which increases the complexity of the snow depth retrieval method for dry snow from the single-pass InSAR data [18]. The repeated-pass InSAR uses the phase of SAR data before and after snowfall to retrieve snow depth, which may suffer from temporal decorrelation, but the repeated-pass InSAR can obtain the phase difference information from before and after snowfall easily, which is the wider application in dry snow depth retrieval [18]. In addition, many studies have retrieved SD using differential interferometric synthetic aperture radar (D-InSAR) methods [20], [21].…”

“…However, compared with forests and glaciers, snow has a smaller thickness and is a dense medium, thus traditional retrieval methods for PolInSAR cannot be directly applied. In recent years, some studies have tried to use PolInSAR to retrieve SD and proved that PolInSAR has great potential in retrieving SD, for example, semi-empirical model [26], CAI model [4], hybrid DEM differencing and coherence amplitude algorithm [27], and dense medium random-volume-over-ground (DM-RVoG) model [18]. Among them, the recently proposed DM-RVoG model involving the dense medium properties of snow is very attractive for retrieving SD.…”