Co-registration and residual correction of digital elevation models: A comparative study
Digital elevation models (DEMs) are currently one of the most widely used data sources in glacier thickness change research, due to the high spatial resolution and continuous coverage. However, raw DEM data are often misaligned with each other, due to georeferencing errors, and a co-registration pro...
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ftcopernicus:oai:publications.copernicus.org:tcd107028 2023-05-15T16:21:32+02:00 Co-registration and residual correction of digital elevation models: A comparative study Li, Tao Hu, Yuanlin Liu, Bin Jiang, Liming Wang, Hansheng Shen, Xiang 2022-11-23 application/pdf https://doi.org/10.5194/tc-2022-205 https://tc.copernicus.org/preprints/tc-2022-205/ eng eng doi:10.5194/tc-2022-205 https://tc.copernicus.org/preprints/tc-2022-205/ eISSN: 1994-0424 Text 2022 ftcopernicus https://doi.org/10.5194/tc-2022-205 2022-11-28T17:22:42Z Digital elevation models (DEMs) are currently one of the most widely used data sources in glacier thickness change research, due to the high spatial resolution and continuous coverage. However, raw DEM data are often misaligned with each other, due to georeferencing errors, and a co-registration procedure is required before DEM differencing. In this paper, we present a comparative analysis of the two classical co-registration methods proposed by Nuth and Kääb (2011) and Rosenholm and Torlegard (1988) . The former is currently the most commonly used method in glacial studies, while the latter is a seminal work in the photogrammetric field that has not been extensively investigated by the cryosphere community. Furthermore, we also present a new residual correction method using a generalized additive model (GAM) to eliminate the remaining systematic errors in DEM co-registration results. The performance of the two DEM co-registration methods and three residual correction algorithms (the GAM-based method together with two parametric-model-based methods) was evaluated using 23 Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM pairs from the western margin of the Greenland Ice Sheet. The experimental results confirm our theoretical analysis of the two co-registration methods. The method of Rosenholm and Torlegard has a greater ability to remove DEM misalignments (4.6 % on average and 15.3 % maximum) because it models the translation, scale, and rotation-induced biases, while the method of Nuth and Kääb considers translation only. The proposed GAM-based method performs statistically better than the two residual correction methods based on parametric regression models (high-order polynomials and the sum of the sinusoidal functions). A visual inspection reveals that the GAM-based method, as a non-parametric regression technique, can capture complex systematic errors in the DEM co-registration residuals. Text glacier Greenland Ice Sheet Copernicus Publications: E-Journals Gam ENVELOPE(-57.955,-57.955,-61.923,-61.923) Greenland |
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Open Polar |
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Copernicus Publications: E-Journals |
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ftcopernicus |
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English |
description |
Digital elevation models (DEMs) are currently one of the most widely used data sources in glacier thickness change research, due to the high spatial resolution and continuous coverage. However, raw DEM data are often misaligned with each other, due to georeferencing errors, and a co-registration procedure is required before DEM differencing. In this paper, we present a comparative analysis of the two classical co-registration methods proposed by Nuth and Kääb (2011) and Rosenholm and Torlegard (1988) . The former is currently the most commonly used method in glacial studies, while the latter is a seminal work in the photogrammetric field that has not been extensively investigated by the cryosphere community. Furthermore, we also present a new residual correction method using a generalized additive model (GAM) to eliminate the remaining systematic errors in DEM co-registration results. The performance of the two DEM co-registration methods and three residual correction algorithms (the GAM-based method together with two parametric-model-based methods) was evaluated using 23 Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM pairs from the western margin of the Greenland Ice Sheet. The experimental results confirm our theoretical analysis of the two co-registration methods. The method of Rosenholm and Torlegard has a greater ability to remove DEM misalignments (4.6 % on average and 15.3 % maximum) because it models the translation, scale, and rotation-induced biases, while the method of Nuth and Kääb considers translation only. The proposed GAM-based method performs statistically better than the two residual correction methods based on parametric regression models (high-order polynomials and the sum of the sinusoidal functions). A visual inspection reveals that the GAM-based method, as a non-parametric regression technique, can capture complex systematic errors in the DEM co-registration residuals. |
format |
Text |
author |
Li, Tao Hu, Yuanlin Liu, Bin Jiang, Liming Wang, Hansheng Shen, Xiang |
spellingShingle |
Li, Tao Hu, Yuanlin Liu, Bin Jiang, Liming Wang, Hansheng Shen, Xiang Co-registration and residual correction of digital elevation models: A comparative study |
author_facet |
Li, Tao Hu, Yuanlin Liu, Bin Jiang, Liming Wang, Hansheng Shen, Xiang |
author_sort |
Li, Tao |
title |
Co-registration and residual correction of digital elevation models: A comparative study |
title_short |
Co-registration and residual correction of digital elevation models: A comparative study |
title_full |
Co-registration and residual correction of digital elevation models: A comparative study |
title_fullStr |
Co-registration and residual correction of digital elevation models: A comparative study |
title_full_unstemmed |
Co-registration and residual correction of digital elevation models: A comparative study |
title_sort |
co-registration and residual correction of digital elevation models: a comparative study |
publishDate |
2022 |
url |
https://doi.org/10.5194/tc-2022-205 https://tc.copernicus.org/preprints/tc-2022-205/ |
long_lat |
ENVELOPE(-57.955,-57.955,-61.923,-61.923) |
geographic |
Gam Greenland |
geographic_facet |
Gam Greenland |
genre |
glacier Greenland Ice Sheet |
genre_facet |
glacier Greenland Ice Sheet |
op_source |
eISSN: 1994-0424 |
op_relation |
doi:10.5194/tc-2022-205 https://tc.copernicus.org/preprints/tc-2022-205/ |
op_doi |
https://doi.org/10.5194/tc-2022-205 |
_version_ |
1766009537991540736 |