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...
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ftethz:oai:www.research-collection.ethz.ch:20.500.11850/426703 2023-05-15T16:29:23+02:00 Modeling and Compensation of the Penetration Bias in InSAR DEMs of Ice Sheets at Different Frequencies Fischer, Georg Papathanassiou, Konstantinos P. Hajnsek, Irena 2020 application/application/pdf https://hdl.handle.net/20.500.11850/426703 https://doi.org/10.3929/ethz-b-000426592 en eng IEEE info:eu-repo/semantics/altIdentifier/doi/10.1109/JSTARS.2020.2992530 info:eu-repo/semantics/altIdentifier/wos/000544047400011 http://hdl.handle.net/20.500.11850/426703 doi:10.3929/ethz-b-000426592 info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International CC-BY IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13 Digital elevation model (DEM) Glaciers Microwave penetration Polarimetric interferometric synthetic aperture radar (Pol-InSAR) Topography info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2020 ftethz https://doi.org/20.500.11850/426703 https://doi.org/10.3929/ethz-b-000426592 https://doi.org/10.1109/JSTARS.2020.2992530 2022-04-25T14:11:12Z 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. ISSN:1939-1404 ISSN:2151-1535 Article in Journal/Newspaper Greenland Ice Sheet ETH Zürich Research Collection Greenland |
institution |
Open Polar |
collection |
ETH Zürich Research Collection |
op_collection_id |
ftethz |
language |
English |
topic |
Digital elevation model (DEM) Glaciers Microwave penetration Polarimetric interferometric synthetic aperture radar (Pol-InSAR) Topography |
spellingShingle |
Digital elevation model (DEM) Glaciers Microwave penetration Polarimetric interferometric synthetic aperture radar (Pol-InSAR) Topography Fischer, Georg Papathanassiou, Konstantinos P. Hajnsek, Irena Modeling and Compensation of the Penetration Bias in InSAR DEMs of Ice Sheets at Different Frequencies |
topic_facet |
Digital elevation model (DEM) Glaciers Microwave penetration Polarimetric interferometric synthetic aperture radar (Pol-InSAR) Topography |
description |
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. ISSN:1939-1404 ISSN:2151-1535 |
format |
Article in Journal/Newspaper |
author |
Fischer, Georg Papathanassiou, Konstantinos P. Hajnsek, Irena |
author_facet |
Fischer, Georg Papathanassiou, Konstantinos P. Hajnsek, Irena |
author_sort |
Fischer, Georg |
title |
Modeling and Compensation of the Penetration Bias in InSAR DEMs of Ice Sheets at Different Frequencies |
title_short |
Modeling and Compensation of the Penetration Bias in InSAR DEMs of Ice Sheets at Different Frequencies |
title_full |
Modeling and Compensation of the Penetration Bias in InSAR DEMs of Ice Sheets at Different Frequencies |
title_fullStr |
Modeling and Compensation of the Penetration Bias in InSAR DEMs of Ice Sheets at Different Frequencies |
title_full_unstemmed |
Modeling and Compensation of the Penetration Bias in InSAR DEMs of Ice Sheets at Different Frequencies |
title_sort |
modeling and compensation of the penetration bias in insar dems of ice sheets at different frequencies |
publisher |
IEEE |
publishDate |
2020 |
url |
https://hdl.handle.net/20.500.11850/426703 https://doi.org/10.3929/ethz-b-000426592 |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Greenland Ice Sheet |
genre_facet |
Greenland Ice Sheet |
op_source |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13 |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1109/JSTARS.2020.2992530 info:eu-repo/semantics/altIdentifier/wos/000544047400011 http://hdl.handle.net/20.500.11850/426703 doi:10.3929/ethz-b-000426592 |
op_rights |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/20.500.11850/426703 https://doi.org/10.3929/ethz-b-000426592 https://doi.org/10.1109/JSTARS.2020.2992530 |
_version_ |
1766019070959812608 |