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Published April 29, 2022 | Accepted Version
Journal Article Open

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

Abstract

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.

Additional Information

© 2022 IEEE. Manuscript received November 4, 2021; revised March 13, 2022; accepted April 18, 2022. Date of publication April 29, 2022; date of current version May 13, 2022. This work was supported in part by the Jet Propulsion Laboratory, California Institute of Technology, under a Contract with the National Aeronautics and Space Administration. The authors would like to thank T. Akins of Remote Sensing Solutions Inc. and R. Shah of JPL for their guidance and support. They would also like to thank the U.S. Government Sponsorship. Copyright 2022. All rights reserved.

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Accepted Version - Dry_snow_parameter_retrieval_with_ground-based_single-pass_Synthetic_Aperture_Radar_Interferometry_acc.pdf

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Dry_snow_parameter_retrieval_with_ground-based_single-pass_Synthetic_Aperture_Radar_Interferometry_acc.pdf

Additional details

Created:
August 22, 2023
Modified:
October 24, 2023