Novel Techniques for Void Filling in Glacier Elevation Change Data Sets
The increasing availability of digital elevation models (DEMs) facilitates the monitoring of glacier mass balances on local and regional scales. Geodetic glacier mass balances are obtained by differentiating DEMs. However, these computations are usually affected by voids in the derived elevation cha...
Published in: | Remote Sensing |
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2020
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Online Access: | https://opus4.kobv.de/opus4-fau/frontdoor/index/index/docId/15414 https://nbn-resolving.org/urn:nbn:de:bvb:29-opus4-154147 https://doi.org/10.3390/rs12233917 https://opus4.kobv.de/opus4-fau/files/15414/remotesensing-12-03917.pdf |
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ftuniverlangen:oai:ub.uni-erlangen.de-opus:15414 2023-05-15T16:20:30+02:00 Novel Techniques for Void Filling in Glacier Elevation Change Data Sets Seehaus, Thorsten Morgenshtern, Veniamin I. Hübner, Fabian Bänsch, Eberhard Braun, Matthias H. 2020-11-29 application/pdf https://opus4.kobv.de/opus4-fau/frontdoor/index/index/docId/15414 https://nbn-resolving.org/urn:nbn:de:bvb:29-opus4-154147 https://doi.org/10.3390/rs12233917 https://opus4.kobv.de/opus4-fau/files/15414/remotesensing-12-03917.pdf eng eng https://opus4.kobv.de/opus4-fau/frontdoor/index/index/docId/15414 urn:nbn:de:bvb:29-opus4-154147 https://nbn-resolving.org/urn:nbn:de:bvb:29-opus4-154147 https://doi.org/10.3390/rs12233917 https://opus4.kobv.de/opus4-fau/files/15414/remotesensing-12-03917.pdf https://creativecommons.org/licenses/by/4.0/deed.de info:eu-repo/semantics/openAccess CC-BY ddc:550 article doc-type:article 2020 ftuniverlangen https://doi.org/10.3390/rs12233917 2022-07-28T20:39:17Z The increasing availability of digital elevation models (DEMs) facilitates the monitoring of glacier mass balances on local and regional scales. Geodetic glacier mass balances are obtained by differentiating DEMs. However, these computations are usually affected by voids in the derived elevation change data sets. Different approaches, using spatial statistics or interpolation techniques, were developed to account for these voids in glacier mass balance estimations. In this study, we apply novel void filling techniques, which are typically used for the reconstruction and retouche of images and photos, for the first time on elevation change maps. We selected 6210 km2 of glacier area in southeast Alaska, USA, covered by two void-free DEMs as the study site to test different inpainting methods. Different artificially voided setups were generated using manually defined voids and a correlation mask based on stereoscopic processing of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) acquisition. Three “novel” (Telea, Navier–Stokes and shearlet) as well as three “classical” (bilinear interpolation, local and global hypsometric methods) void filling approaches for glacier elevation data sets were implemented and evaluated. The hypsometric approaches showed, in general, the worst performance, leading to high average and local offsets. Telea and Navier–Stokes void filling showed an overall stable and reasonable quality. The best results are obtained for shearlet and bilinear void filling, if certain criteria are met. Considering also computational costs and feasibility, we recommend using the bilinear void filling method in glacier volume change analyses. Moreover, we propose and validate a formula to estimate the uncertainties caused by void filling in glacier volume change computations. The formula is transferable to other study sites, where no ground truth data on the void areas exist, and leads to higher accuracy of the error estimates on void-filled areas. In the spirit of reproducible research, ... Article in Journal/Newspaper glacier Alaska OPUS FAU - Online publication system of Friedrich-Alexander-Universität Erlangen-Nürnberg Geodetic Glacier ENVELOPE(163.800,163.800,-77.750,-77.750) Remote Sensing 12 23 3917 |
institution |
Open Polar |
collection |
OPUS FAU - Online publication system of Friedrich-Alexander-Universität Erlangen-Nürnberg |
op_collection_id |
ftuniverlangen |
language |
English |
topic |
ddc:550 |
spellingShingle |
ddc:550 Seehaus, Thorsten Morgenshtern, Veniamin I. Hübner, Fabian Bänsch, Eberhard Braun, Matthias H. Novel Techniques for Void Filling in Glacier Elevation Change Data Sets |
topic_facet |
ddc:550 |
description |
The increasing availability of digital elevation models (DEMs) facilitates the monitoring of glacier mass balances on local and regional scales. Geodetic glacier mass balances are obtained by differentiating DEMs. However, these computations are usually affected by voids in the derived elevation change data sets. Different approaches, using spatial statistics or interpolation techniques, were developed to account for these voids in glacier mass balance estimations. In this study, we apply novel void filling techniques, which are typically used for the reconstruction and retouche of images and photos, for the first time on elevation change maps. We selected 6210 km2 of glacier area in southeast Alaska, USA, covered by two void-free DEMs as the study site to test different inpainting methods. Different artificially voided setups were generated using manually defined voids and a correlation mask based on stereoscopic processing of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) acquisition. Three “novel” (Telea, Navier–Stokes and shearlet) as well as three “classical” (bilinear interpolation, local and global hypsometric methods) void filling approaches for glacier elevation data sets were implemented and evaluated. The hypsometric approaches showed, in general, the worst performance, leading to high average and local offsets. Telea and Navier–Stokes void filling showed an overall stable and reasonable quality. The best results are obtained for shearlet and bilinear void filling, if certain criteria are met. Considering also computational costs and feasibility, we recommend using the bilinear void filling method in glacier volume change analyses. Moreover, we propose and validate a formula to estimate the uncertainties caused by void filling in glacier volume change computations. The formula is transferable to other study sites, where no ground truth data on the void areas exist, and leads to higher accuracy of the error estimates on void-filled areas. In the spirit of reproducible research, ... |
format |
Article in Journal/Newspaper |
author |
Seehaus, Thorsten Morgenshtern, Veniamin I. Hübner, Fabian Bänsch, Eberhard Braun, Matthias H. |
author_facet |
Seehaus, Thorsten Morgenshtern, Veniamin I. Hübner, Fabian Bänsch, Eberhard Braun, Matthias H. |
author_sort |
Seehaus, Thorsten |
title |
Novel Techniques for Void Filling in Glacier Elevation Change Data Sets |
title_short |
Novel Techniques for Void Filling in Glacier Elevation Change Data Sets |
title_full |
Novel Techniques for Void Filling in Glacier Elevation Change Data Sets |
title_fullStr |
Novel Techniques for Void Filling in Glacier Elevation Change Data Sets |
title_full_unstemmed |
Novel Techniques for Void Filling in Glacier Elevation Change Data Sets |
title_sort |
novel techniques for void filling in glacier elevation change data sets |
publishDate |
2020 |
url |
https://opus4.kobv.de/opus4-fau/frontdoor/index/index/docId/15414 https://nbn-resolving.org/urn:nbn:de:bvb:29-opus4-154147 https://doi.org/10.3390/rs12233917 https://opus4.kobv.de/opus4-fau/files/15414/remotesensing-12-03917.pdf |
long_lat |
ENVELOPE(163.800,163.800,-77.750,-77.750) |
geographic |
Geodetic Glacier |
geographic_facet |
Geodetic Glacier |
genre |
glacier Alaska |
genre_facet |
glacier Alaska |
op_relation |
https://opus4.kobv.de/opus4-fau/frontdoor/index/index/docId/15414 urn:nbn:de:bvb:29-opus4-154147 https://nbn-resolving.org/urn:nbn:de:bvb:29-opus4-154147 https://doi.org/10.3390/rs12233917 https://opus4.kobv.de/opus4-fau/files/15414/remotesensing-12-03917.pdf |
op_rights |
https://creativecommons.org/licenses/by/4.0/deed.de info:eu-repo/semantics/openAccess |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.3390/rs12233917 |
container_title |
Remote Sensing |
container_volume |
12 |
container_issue |
23 |
container_start_page |
3917 |
_version_ |
1766008427194089472 |