Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping
Snow depth has traditionally been estimated based on point measurements collected either manually or at automated weather stations. Point measurements, though, do not represent the high spatial variability in snow depths present in alpine terrain. Photogrammetric mapping techniques have progressed i...
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Copernicus Publications
2021
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ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00054929 2023-05-15T18:32:32+02:00 Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping Eberhard, Lucie A. Sirguey, Pascal Miller, Aubrey Marty, Mauro Schindler, Konrad Stoffel, Andreas Bühler, Yves 2021-01 electronic https://doi.org/10.5194/tc-15-69-2021 https://noa.gwlb.de/receive/cop_mods_00054929 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00054580/tc-15-69-2021.pdf https://tc.copernicus.org/articles/15/69/2021/tc-15-69-2021.pdf eng eng Copernicus Publications The Cryosphere -- ˜Theœ Cryosphere -- http://www.bibliothek.uni-regensburg.de/ezeit/?2393169 -- http://www.the-cryosphere.net/ -- 1994-0424 https://doi.org/10.5194/tc-15-69-2021 https://noa.gwlb.de/receive/cop_mods_00054929 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00054580/tc-15-69-2021.pdf https://tc.copernicus.org/articles/15/69/2021/tc-15-69-2021.pdf https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess CC-BY article Verlagsveröffentlichung article Text doc-type:article 2021 ftnonlinearchiv https://doi.org/10.5194/tc-15-69-2021 2022-02-08T22:34:45Z Snow depth has traditionally been estimated based on point measurements collected either manually or at automated weather stations. Point measurements, though, do not represent the high spatial variability in snow depths present in alpine terrain. Photogrammetric mapping techniques have progressed in recent years and are capable of accurately mapping snow depth in a spatially continuous manner, over larger areas and at various spatial resolutions. However, the strengths and weaknesses associated with specific platforms and photogrammetric techniques as well as the accuracy of the photogrammetric performance on snow surfaces have not yet been sufficiently investigated. Therefore, industry-standard photogrammetric platforms, including high-resolution satellite (Pléiades), airplane (Ultracam Eagle M3), unmanned aerial system (eBee+ RTK with SenseFly S.O.D.A. camera) and terrestrial (single lens reflex camera, Canon EOS 750D) platforms, were tested for snow depth mapping in the alpine Dischma valley (Switzerland) in spring 2018. Imagery was acquired with airborne and space-borne platforms over the entire valley, while unmanned aerial system (UAS) and terrestrial photogrammetric imagery was acquired over a subset of the valley. For independent validation of the photogrammetric products, snow depth was measured by probing as well as by using remote observations of fixed snow poles. When comparing snow depth maps with manual and snow pole measurements, the root mean square error (RMSE) values and the normalized median absolute deviation (NMAD) values were 0.52 and 0.47 m, respectively, for the satellite snow depth map, 0.17 and 0.17 m for the airplane snow depth map, and 0.16 and 0.11 m for the UAS snow depth map. The area covered by the terrestrial snow depth map only intersected with four manual measurements and did not generate statistically relevant measurements. When using the UAS snow depth map as a reference surface, the RMSE and NMAD values were 0.44 and 0.38 m for the satellite snow depth map, 0.12 and 0.11 m for the airplane snow depth map, and 0.21 and 0.19 m for the terrestrial snow depth map. When compared to the airplane dataset over a large part of the Dischma valley (40 km2), the snow depth map from the satellite yielded an RMSE value of 0.92 m and an NMAD value of 0.65 m. This study provides comparative measurements between photogrammetric platforms to evaluate their specific advantages and disadvantages for operational, spatially continuous snow depth mapping in alpine terrain over both small and large geographic areas. Article in Journal/Newspaper The Cryosphere Niedersächsisches Online-Archiv NOA The Cryosphere 15 1 69 94 |
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Niedersächsisches Online-Archiv NOA |
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English |
topic |
article Verlagsveröffentlichung |
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article Verlagsveröffentlichung Eberhard, Lucie A. Sirguey, Pascal Miller, Aubrey Marty, Mauro Schindler, Konrad Stoffel, Andreas Bühler, Yves Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping |
topic_facet |
article Verlagsveröffentlichung |
description |
Snow depth has traditionally been estimated based on point measurements collected either manually or at automated weather stations. Point measurements, though, do not represent the high spatial variability in snow depths present in alpine terrain. Photogrammetric mapping techniques have progressed in recent years and are capable of accurately mapping snow depth in a spatially continuous manner, over larger areas and at various spatial resolutions. However, the strengths and weaknesses associated with specific platforms and photogrammetric techniques as well as the accuracy of the photogrammetric performance on snow surfaces have not yet been sufficiently investigated. Therefore, industry-standard photogrammetric platforms, including high-resolution satellite (Pléiades), airplane (Ultracam Eagle M3), unmanned aerial system (eBee+ RTK with SenseFly S.O.D.A. camera) and terrestrial (single lens reflex camera, Canon EOS 750D) platforms, were tested for snow depth mapping in the alpine Dischma valley (Switzerland) in spring 2018. Imagery was acquired with airborne and space-borne platforms over the entire valley, while unmanned aerial system (UAS) and terrestrial photogrammetric imagery was acquired over a subset of the valley. For independent validation of the photogrammetric products, snow depth was measured by probing as well as by using remote observations of fixed snow poles. When comparing snow depth maps with manual and snow pole measurements, the root mean square error (RMSE) values and the normalized median absolute deviation (NMAD) values were 0.52 and 0.47 m, respectively, for the satellite snow depth map, 0.17 and 0.17 m for the airplane snow depth map, and 0.16 and 0.11 m for the UAS snow depth map. The area covered by the terrestrial snow depth map only intersected with four manual measurements and did not generate statistically relevant measurements. When using the UAS snow depth map as a reference surface, the RMSE and NMAD values were 0.44 and 0.38 m for the satellite snow depth map, 0.12 and 0.11 m for the airplane snow depth map, and 0.21 and 0.19 m for the terrestrial snow depth map. When compared to the airplane dataset over a large part of the Dischma valley (40 km2), the snow depth map from the satellite yielded an RMSE value of 0.92 m and an NMAD value of 0.65 m. This study provides comparative measurements between photogrammetric platforms to evaluate their specific advantages and disadvantages for operational, spatially continuous snow depth mapping in alpine terrain over both small and large geographic areas. |
format |
Article in Journal/Newspaper |
author |
Eberhard, Lucie A. Sirguey, Pascal Miller, Aubrey Marty, Mauro Schindler, Konrad Stoffel, Andreas Bühler, Yves |
author_facet |
Eberhard, Lucie A. Sirguey, Pascal Miller, Aubrey Marty, Mauro Schindler, Konrad Stoffel, Andreas Bühler, Yves |
author_sort |
Eberhard, Lucie A. |
title |
Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping |
title_short |
Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping |
title_full |
Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping |
title_fullStr |
Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping |
title_full_unstemmed |
Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping |
title_sort |
intercomparison of photogrammetric platforms for spatially continuous snow depth mapping |
publisher |
Copernicus Publications |
publishDate |
2021 |
url |
https://doi.org/10.5194/tc-15-69-2021 https://noa.gwlb.de/receive/cop_mods_00054929 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00054580/tc-15-69-2021.pdf https://tc.copernicus.org/articles/15/69/2021/tc-15-69-2021.pdf |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_relation |
The Cryosphere -- ˜Theœ Cryosphere -- http://www.bibliothek.uni-regensburg.de/ezeit/?2393169 -- http://www.the-cryosphere.net/ -- 1994-0424 https://doi.org/10.5194/tc-15-69-2021 https://noa.gwlb.de/receive/cop_mods_00054929 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00054580/tc-15-69-2021.pdf https://tc.copernicus.org/articles/15/69/2021/tc-15-69-2021.pdf |
op_rights |
https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.5194/tc-15-69-2021 |
container_title |
The Cryosphere |
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15 |
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1 |
container_start_page |
69 |
op_container_end_page |
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