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The differential SAR interferometry (DInSAR) phase can be approximated as a linear function of the snow water equivalent (SWE) changes in snow depth and density. The SWE estimation from DInSAR phase presents some criticalities related both to the penetration of the SAR signal into the snowpack, and the nature of interferometric measurements. This work revises some of the issues related to the SWE estimation, and experiments the use of multifrequency SAR data for deriving SWE maps over Alpine areas. Preliminarily, we performed a theoretical analysis aimed at assessing the performance of DInSAR-based SWE estimation at X, C and L bands. According to the indications coming from this analysis C and L band are the more promising to overcome some of the factors limiting the SWE estimation. A dataset of 345 Sentinel-1 images was selected with the aim to explore the interferometric coherence over time and to exploit the short revisit time of the Sentinel-1 constellation. SAOCOM data were also used, for taking advantage of the long L-band wavelength, which should guarantee SAR penetration into the snowpack, snow homogeneity, suitable values of interferometric coherence, and low probability of phase aliasing. The datasets were processed by adopting a “cascaded” interferogram formation approach. Atmosphere artifacts were removed by using the zenith total delay maps derived by GACOS. In order to select pixels suitable for performing a valuable SWE estimation, a sensibility map was generated for each interferometric pair. Both Sentinel-1 and SAOCOM datasets selected over the test cases were processes according to described processing strategy. The SWE estimations resulting from C- and L-band data were combined and analysed looking at their behavior in space and time.
- Acknowledgments - This work was carried out in the framework of the project “CRIOSAR: Applicazioni SAR multifrequenza alla criosfera”, funded by ASI under grant agreement n. ASI N. 2021-12-U.0.
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