Validation of TanDEM-X Surface Elevation on Devon Island Ice Cap
Remotely sensed surface elevation datasets are key to study mass balance and dynamic behaviours of glaciers, ice caps and ice sheets. Digital elevation models (DEM) generated from the TanDEM-X mission from single pass synthetic aperture radar interferometry (InSAR) at X-band provide an excellent pot...
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ftdlr:oai:elib.dlr.de:129957 2024-05-19T07:35:49+00:00 Validation of TanDEM-X Surface Elevation on Devon Island Ice Cap Bernard-Grand'Maison, Claire Burgess, David Copeland, Luke Abdullahi, Sahra Wessel, Birgit Rutishauser, Anja Blankenship, D.D. Young, Duncan 2019 https://elib.dlr.de/129957/ unknown Bernard-Grand'Maison, Claire und Burgess, David und Copeland, Luke und Abdullahi, Sahra und Wessel, Birgit und Rutishauser, Anja und Blankenship, D.D. und Young, Duncan (2019) Validation of TanDEM-X Surface Elevation on Devon Island Ice Cap. IUGG 2019, 2019-07-08 - 2019-07-18, Montreal, Canada. Dynamik der Landoberfläche Konferenzbeitrag NonPeerReviewed 2019 ftdlr 2024-04-25T00:51:33Z Remotely sensed surface elevation datasets are key to study mass balance and dynamic behaviours of glaciers, ice caps and ice sheets. Digital elevation models (DEM) generated from the TanDEM-X mission from single pass synthetic aperture radar interferometry (InSAR) at X-band provide an excellent potential resource for this purpose. However, they typically suffer from a negative bias in calculated surface elevations on glaciers due to penetration of radar waves in the snowpack and firn layers. Penetration depth depends on snowpack properties and acquisition parameters, and can be estimated using a simple model based on backscatter intensity, interferometric coherence and height of ambiguity parameters. To validate modelled penetration depths, multiple concurrent acquisitions of TanDEM-X images with ground measurements, airborne campaigns and spaceborne derived surface elevations were completed over Devon Island Ice Cap (75.25° N, 82.5° W) in the Canadian Arctic. Comparison of three TanDEM-X mosaic DEMs (winter 2010/11, 2013/14 and spring 2018) with differential GPS measurements (2011 and 2018), laser altimetry surveys (NASA ATM 2011 and SEARCH data 2018), and the Arctic DEM (2014), reveal an elevation bias of approximatively -3 m wherever firn layers are present below the snowpack. In this talk, we present corrected surface elevations for Devon Island Ice Cap and assess the spatial variability of penetration depths in relation to surface conditions and measured radar parameters. This validation case study improves the modelling of penetration depth for future application in all TanDEM-X DEMs over glaciated terrain. Conference Object Arctic Devon Island Ice cap German Aerospace Center: elib - DLR electronic library |
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Open Polar |
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German Aerospace Center: elib - DLR electronic library |
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Dynamik der Landoberfläche |
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Dynamik der Landoberfläche Bernard-Grand'Maison, Claire Burgess, David Copeland, Luke Abdullahi, Sahra Wessel, Birgit Rutishauser, Anja Blankenship, D.D. Young, Duncan Validation of TanDEM-X Surface Elevation on Devon Island Ice Cap |
topic_facet |
Dynamik der Landoberfläche |
description |
Remotely sensed surface elevation datasets are key to study mass balance and dynamic behaviours of glaciers, ice caps and ice sheets. Digital elevation models (DEM) generated from the TanDEM-X mission from single pass synthetic aperture radar interferometry (InSAR) at X-band provide an excellent potential resource for this purpose. However, they typically suffer from a negative bias in calculated surface elevations on glaciers due to penetration of radar waves in the snowpack and firn layers. Penetration depth depends on snowpack properties and acquisition parameters, and can be estimated using a simple model based on backscatter intensity, interferometric coherence and height of ambiguity parameters. To validate modelled penetration depths, multiple concurrent acquisitions of TanDEM-X images with ground measurements, airborne campaigns and spaceborne derived surface elevations were completed over Devon Island Ice Cap (75.25° N, 82.5° W) in the Canadian Arctic. Comparison of three TanDEM-X mosaic DEMs (winter 2010/11, 2013/14 and spring 2018) with differential GPS measurements (2011 and 2018), laser altimetry surveys (NASA ATM 2011 and SEARCH data 2018), and the Arctic DEM (2014), reveal an elevation bias of approximatively -3 m wherever firn layers are present below the snowpack. In this talk, we present corrected surface elevations for Devon Island Ice Cap and assess the spatial variability of penetration depths in relation to surface conditions and measured radar parameters. This validation case study improves the modelling of penetration depth for future application in all TanDEM-X DEMs over glaciated terrain. |
format |
Conference Object |
author |
Bernard-Grand'Maison, Claire Burgess, David Copeland, Luke Abdullahi, Sahra Wessel, Birgit Rutishauser, Anja Blankenship, D.D. Young, Duncan |
author_facet |
Bernard-Grand'Maison, Claire Burgess, David Copeland, Luke Abdullahi, Sahra Wessel, Birgit Rutishauser, Anja Blankenship, D.D. Young, Duncan |
author_sort |
Bernard-Grand'Maison, Claire |
title |
Validation of TanDEM-X Surface Elevation on Devon Island Ice Cap |
title_short |
Validation of TanDEM-X Surface Elevation on Devon Island Ice Cap |
title_full |
Validation of TanDEM-X Surface Elevation on Devon Island Ice Cap |
title_fullStr |
Validation of TanDEM-X Surface Elevation on Devon Island Ice Cap |
title_full_unstemmed |
Validation of TanDEM-X Surface Elevation on Devon Island Ice Cap |
title_sort |
validation of tandem-x surface elevation on devon island ice cap |
publishDate |
2019 |
url |
https://elib.dlr.de/129957/ |
genre |
Arctic Devon Island Ice cap |
genre_facet |
Arctic Devon Island Ice cap |
op_relation |
Bernard-Grand'Maison, Claire und Burgess, David und Copeland, Luke und Abdullahi, Sahra und Wessel, Birgit und Rutishauser, Anja und Blankenship, D.D. und Young, Duncan (2019) Validation of TanDEM-X Surface Elevation on Devon Island Ice Cap. IUGG 2019, 2019-07-08 - 2019-07-18, Montreal, Canada. |
_version_ |
1799474833994547200 |