Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data
The unprecedented precision of satellite laser altimetry data from the NASA ICESat-2 mission and the increasing availability of high-resolution elevation datasets open new opportunities to measure snow depth in mountains, a critical variable for ecosystem and water resource monitoring. We retrieved...
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ftdoajarticles:oai:doaj.org/article:0c1142cb1dd0424092f75f3d102457e4 2023-07-30T04:07:15+02:00 Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data C. Deschamps-Berger S. Gascoin D. Shean H. Besso A. Guiot J. I. López-Moreno 2023-07-01T00:00:00Z https://doi.org/10.5194/tc-17-2779-2023 https://doaj.org/article/0c1142cb1dd0424092f75f3d102457e4 EN eng Copernicus Publications https://tc.copernicus.org/articles/17/2779/2023/tc-17-2779-2023.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-17-2779-2023 1994-0416 1994-0424 https://doaj.org/article/0c1142cb1dd0424092f75f3d102457e4 The Cryosphere, Vol 17, Pp 2779-2792 (2023) Environmental sciences GE1-350 Geology QE1-996.5 article 2023 ftdoajarticles https://doi.org/10.5194/tc-17-2779-2023 2023-07-16T00:35:52Z The unprecedented precision of satellite laser altimetry data from the NASA ICESat-2 mission and the increasing availability of high-resolution elevation datasets open new opportunities to measure snow depth in mountains, a critical variable for ecosystem and water resource monitoring. We retrieved snow depth over the upper Tuolumne basin (California, USA) for 3 years by differencing ICESat-2 ATL06 snow-on elevations and various snow-off digital elevation models. Snow depth derived from ATL06 data only (snow-on and snow-off) offers a poor temporal and spatial coverage, limiting its potential utility. However, using a digital terrain model from airborne lidar surveys as the snow-off elevation source yielded a snow depth accuracy of ∼ 0.2 m (bias) and precision of ∼ 1 m (random error) across the basin, with an improved precision of 0.5 m for low slopes ( < 10 ∘ ), compared to eight reference airborne lidar snow depth maps. Snow depths derived from ICESat-2 ATL06 and a satellite photogrammetry digital elevation model have a larger bias and reduced precision, partly induced by increased errors in forested areas. These various combinations of repeated ICESat-2 snow surface elevation measurements with satellite or airborne products will enable tailored approaches to map snow depth and estimate water resource availability in mountainous areas with limited snow depth observations. Article in Journal/Newspaper The Cryosphere Directory of Open Access Journals: DOAJ Articles The Cryosphere 17 7 2779 2792 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Environmental sciences GE1-350 Geology QE1-996.5 |
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Environmental sciences GE1-350 Geology QE1-996.5 C. Deschamps-Berger S. Gascoin D. Shean H. Besso A. Guiot J. I. López-Moreno Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data |
topic_facet |
Environmental sciences GE1-350 Geology QE1-996.5 |
description |
The unprecedented precision of satellite laser altimetry data from the NASA ICESat-2 mission and the increasing availability of high-resolution elevation datasets open new opportunities to measure snow depth in mountains, a critical variable for ecosystem and water resource monitoring. We retrieved snow depth over the upper Tuolumne basin (California, USA) for 3 years by differencing ICESat-2 ATL06 snow-on elevations and various snow-off digital elevation models. Snow depth derived from ATL06 data only (snow-on and snow-off) offers a poor temporal and spatial coverage, limiting its potential utility. However, using a digital terrain model from airborne lidar surveys as the snow-off elevation source yielded a snow depth accuracy of ∼ 0.2 m (bias) and precision of ∼ 1 m (random error) across the basin, with an improved precision of 0.5 m for low slopes ( < 10 ∘ ), compared to eight reference airborne lidar snow depth maps. Snow depths derived from ICESat-2 ATL06 and a satellite photogrammetry digital elevation model have a larger bias and reduced precision, partly induced by increased errors in forested areas. These various combinations of repeated ICESat-2 snow surface elevation measurements with satellite or airborne products will enable tailored approaches to map snow depth and estimate water resource availability in mountainous areas with limited snow depth observations. |
format |
Article in Journal/Newspaper |
author |
C. Deschamps-Berger S. Gascoin D. Shean H. Besso A. Guiot J. I. López-Moreno |
author_facet |
C. Deschamps-Berger S. Gascoin D. Shean H. Besso A. Guiot J. I. López-Moreno |
author_sort |
C. Deschamps-Berger |
title |
Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data |
title_short |
Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data |
title_full |
Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data |
title_fullStr |
Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data |
title_full_unstemmed |
Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data |
title_sort |
evaluation of snow depth retrievals from icesat-2 using airborne laser-scanning data |
publisher |
Copernicus Publications |
publishDate |
2023 |
url |
https://doi.org/10.5194/tc-17-2779-2023 https://doaj.org/article/0c1142cb1dd0424092f75f3d102457e4 |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
The Cryosphere, Vol 17, Pp 2779-2792 (2023) |
op_relation |
https://tc.copernicus.org/articles/17/2779/2023/tc-17-2779-2023.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-17-2779-2023 1994-0416 1994-0424 https://doaj.org/article/0c1142cb1dd0424092f75f3d102457e4 |
op_doi |
https://doi.org/10.5194/tc-17-2779-2023 |
container_title |
The Cryosphere |
container_volume |
17 |
container_issue |
7 |
container_start_page |
2779 |
op_container_end_page |
2792 |
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