Modeling and Compensation of the Penetration Bias in InSAR DEMs of Ice Sheets at Different Frequencies
Interferometric synthetic aperture radar (InSAR) is able to provide important information for the characterization of the surface topography of glaciers and ice sheets. However, due to the inherent penetration of microwaves into dry snow, firn, and ice, InSAR elevation models are affected by a penet...
| Published in: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Main Authors: | , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
IEEE
2020
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| Subjects: | |
| Online Access: | https://doi.org/10.1109/JSTARS.2020.2992530 https://doaj.org/article/70f384628e304f539909f97fb6338667 |
| Summary: | Interferometric synthetic aperture radar (InSAR) is able to provide important information for the characterization of the surface topography of glaciers and ice sheets. However, due to the inherent penetration of microwaves into dry snow, firn, and ice, InSAR elevation models are affected by a penetration bias. The fact that this bias depends on the snow and ice conditions as well as on the interferometric acquisition parameters complicates its assessment and makes it also relevant for measuring topographic changes. Recent studies indicated the potential for model-based compensation of this penetration bias. This article follows this approach and investigates the performance of two subsurface volume models for this task. Single-channel and polarimetric approaches are discussed for random and oriented volume scenarios. The model performance is assessed on two test sites in the percolation zone of the Greenland ice sheet using fully polarimetric airborne X-, C-, L-, and P-band InSAR data. The results indicate that simple models can partially compensate the penetration bias and provide more accurate topographic information than the interferometric phase center measurements alone. |
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