Correlation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements
In recent years a vast amount of glacier surface velocity data from satellite imagery has emerged based on correlation between repeat images. Thereby, much emphasis has been put on the fast processing of large data volumes and products with complete spatial coverage. The metadata of such measurement...
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Copernicus Publications under license by EGU – European Geosciences Union GmbH
2022
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Online Access: | http://hdl.handle.net/10852/99272 https://doi.org/10.5194/tc-16-2285-2022 |
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ftoslouniv:oai:www.duo.uio.no:10852/99272 2023-05-15T16:20:34+02:00 Correlation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements ENEngelskEnglishCorrelation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements Altena, Bas Kääb, Andreas Wouters, Bert 2022-09-20T09:24:20Z http://hdl.handle.net/10852/99272 https://doi.org/10.5194/tc-16-2285-2022 EN eng Copernicus Publications under license by EGU – European Geosciences Union GmbH Altena, Bas Kääb, Andreas Wouters, Bert . Correlation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements. The Cryosphere. 2022, 16(6), 2285-2300 http://hdl.handle.net/10852/99272 2053335 info:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=The Cryosphere&rft.volume=16&rft.spage=2285&rft.date=2022 The Cryosphere 16 6 2285 2300 https://doi.org/10.5194/tc-16-2285-2022 Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/ CC-BY 1994-0416 Journal article Tidsskriftartikkel Peer reviewed PublishedVersion 2022 ftoslouniv https://doi.org/10.5194/tc-16-2285-2022 2023-02-01T23:36:26Z In recent years a vast amount of glacier surface velocity data from satellite imagery has emerged based on correlation between repeat images. Thereby, much emphasis has been put on the fast processing of large data volumes and products with complete spatial coverage. The metadata of such measurements are often highly simplified when the measurement precision is lumped into a single number for the whole dataset, although the error budget of image matching is in reality neither isotropic nor constant over the whole velocity field. The spread of the correlation peak of individual image offset measurements is dependent on the image structure and the non-uniform flow of the ice and is used here to extract a proxy for measurement uncertainty. A quantification of estimation error or dispersion for each individual velocity measurement can be important for the inversion of, for instance, rheology, ice thickness and/or bedrock friction. Errors in the velocity data can propagate into derived results in a complex and exaggerating way, making the outcomes very sensitive to velocity noise and outliers. Here, we present a computationally fast method to estimate the matching precision of individual displacement measurements from repeat imaging data, focusing on satellite data. The approach is based upon Gaussian fitting directly on the correlation peak and is formulated as a linear least-squares estimation, making its implementation into current pipelines straightforward. The methodology is demonstrated for Sermeq Kujalleq (Jakobshavn Isbræ), Greenland, a glacier with regions of strong shear flow and with clearly oriented crevasses, and Malaspina Glacier, Alaska. Directionality within an image seems to be the dominant factor influencing the correlation dispersion. In our cases these are crevasses and moraine bands, while a relation to differential flow, such as shear, is less pronounced on the correlation spread. Article in Journal/Newspaper glacier glacier Greenland Jakobshavn Jakobshavn isbræ Kujalleq Sermeq Kujalleq The Cryosphere Alaska Universitet i Oslo: Digitale utgivelser ved UiO (DUO) Greenland Jakobshavn Isbræ ENVELOPE(-49.917,-49.917,69.167,69.167) Kujalleq ENVELOPE(-46.037,-46.037,60.719,60.719) The Cryosphere 16 6 2285 2300 |
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Open Polar |
collection |
Universitet i Oslo: Digitale utgivelser ved UiO (DUO) |
op_collection_id |
ftoslouniv |
language |
English |
description |
In recent years a vast amount of glacier surface velocity data from satellite imagery has emerged based on correlation between repeat images. Thereby, much emphasis has been put on the fast processing of large data volumes and products with complete spatial coverage. The metadata of such measurements are often highly simplified when the measurement precision is lumped into a single number for the whole dataset, although the error budget of image matching is in reality neither isotropic nor constant over the whole velocity field. The spread of the correlation peak of individual image offset measurements is dependent on the image structure and the non-uniform flow of the ice and is used here to extract a proxy for measurement uncertainty. A quantification of estimation error or dispersion for each individual velocity measurement can be important for the inversion of, for instance, rheology, ice thickness and/or bedrock friction. Errors in the velocity data can propagate into derived results in a complex and exaggerating way, making the outcomes very sensitive to velocity noise and outliers. Here, we present a computationally fast method to estimate the matching precision of individual displacement measurements from repeat imaging data, focusing on satellite data. The approach is based upon Gaussian fitting directly on the correlation peak and is formulated as a linear least-squares estimation, making its implementation into current pipelines straightforward. The methodology is demonstrated for Sermeq Kujalleq (Jakobshavn Isbræ), Greenland, a glacier with regions of strong shear flow and with clearly oriented crevasses, and Malaspina Glacier, Alaska. Directionality within an image seems to be the dominant factor influencing the correlation dispersion. In our cases these are crevasses and moraine bands, while a relation to differential flow, such as shear, is less pronounced on the correlation spread. |
format |
Article in Journal/Newspaper |
author |
Altena, Bas Kääb, Andreas Wouters, Bert |
spellingShingle |
Altena, Bas Kääb, Andreas Wouters, Bert Correlation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements |
author_facet |
Altena, Bas Kääb, Andreas Wouters, Bert |
author_sort |
Altena, Bas |
title |
Correlation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements |
title_short |
Correlation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements |
title_full |
Correlation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements |
title_fullStr |
Correlation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements |
title_full_unstemmed |
Correlation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements |
title_sort |
correlation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements |
publisher |
Copernicus Publications under license by EGU – European Geosciences Union GmbH |
publishDate |
2022 |
url |
http://hdl.handle.net/10852/99272 https://doi.org/10.5194/tc-16-2285-2022 |
long_lat |
ENVELOPE(-49.917,-49.917,69.167,69.167) ENVELOPE(-46.037,-46.037,60.719,60.719) |
geographic |
Greenland Jakobshavn Isbræ Kujalleq |
geographic_facet |
Greenland Jakobshavn Isbræ Kujalleq |
genre |
glacier glacier Greenland Jakobshavn Jakobshavn isbræ Kujalleq Sermeq Kujalleq The Cryosphere Alaska |
genre_facet |
glacier glacier Greenland Jakobshavn Jakobshavn isbræ Kujalleq Sermeq Kujalleq The Cryosphere Alaska |
op_source |
1994-0416 |
op_relation |
Altena, Bas Kääb, Andreas Wouters, Bert . Correlation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements. The Cryosphere. 2022, 16(6), 2285-2300 http://hdl.handle.net/10852/99272 2053335 info:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=The Cryosphere&rft.volume=16&rft.spage=2285&rft.date=2022 The Cryosphere 16 6 2285 2300 https://doi.org/10.5194/tc-16-2285-2022 |
op_rights |
Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/ |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.5194/tc-16-2285-2022 |
container_title |
The Cryosphere |
container_volume |
16 |
container_issue |
6 |
container_start_page |
2285 |
op_container_end_page |
2300 |
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1766008489517252608 |