Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data

Accurate knowledge of snow depth distributions in mountain catchments is critical for applications in hydrology and ecology. Recently, a method was proposed to map snow depth at meter-scale resolution from very-high-resolution stereo satellite imagery (e.g., Pléiades) with an accuracy close to 0.5 m...

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Main Authors: Deschamps-Berger, César, Gascoin, Simon, Berthier, Etienne, Deems, Jeffrey, Gutmann, Ethan, Dehecq, Amaury, Shean, David, Dumont, Marie
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus 2020
Subjects:
Online Access:https://hdl.handle.net/20.500.11850/444952
https://doi.org/10.3929/ethz-b-000444952
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spelling ftethz:oai:www.research-collection.ethz.ch:20.500.11850/444952 2023-05-15T18:32:14+02:00 Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data Deschamps-Berger, César Gascoin, Simon Berthier, Etienne Deems, Jeffrey Gutmann, Ethan Dehecq, Amaury Shean, David Dumont, Marie 2020 application/application/pdf https://hdl.handle.net/20.500.11850/444952 https://doi.org/10.3929/ethz-b-000444952 en eng Copernicus info:eu-repo/semantics/altIdentifier/doi/10.5194/tc-14-2925-2020 info:eu-repo/semantics/altIdentifier/wos/000571465800001 http://hdl.handle.net/20.500.11850/444952 doi:10.3929/ethz-b-000444952 info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International CC-BY The Cryosphere, 14 (9) info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2020 ftethz https://doi.org/20.500.11850/444952 https://doi.org/10.3929/ethz-b-000444952 https://doi.org/10.5194/tc-14-2925-2020 2022-04-25T14:14:30Z Accurate knowledge of snow depth distributions in mountain catchments is critical for applications in hydrology and ecology. Recently, a method was proposed to map snow depth at meter-scale resolution from very-high-resolution stereo satellite imagery (e.g., Pléiades) with an accuracy close to 0.5 m. However, the validation was limited to probe measurements and unmanned aircraft vehicle (UAV) photogrammetry, which sampled a limited fraction of the topographic and snow depth variability. We improve upon this evaluation using accurate maps of the snow depth derived from Airborne Snow Observatory laser-scanning measurements in the Tuolumne river basin, USA. We find a good agreement between both datasets over a snow-covered area of 138 km2 on a 3 m grid, with a positive bias for a Pléiades snow depth of 0.08 m, a root mean square error of 0.80 m and a normalized median absolute deviation (NMAD) of 0.69 m. Satellite data capture the relationship between snow depth and elevation at the catchment scale and also small-scale features like snow drifts and avalanche deposits at a typical scale of tens of meters. The random error at the pixel level is lower in snow-free areas than in snow-covered areas, but it is reduced by a factor of 2 (NMAD of approximately 0.40 m for snow depth) when averaged to a 36 m grid. We conclude that satellite photogrammetry stands out as a convenient method to estimate the spatial distribution of snow depth in high mountain catchments. ISSN:1994-0416 ISSN:1994-0424 Article in Journal/Newspaper The Cryosphere ETH Zürich Research Collection
institution Open Polar
collection ETH Zürich Research Collection
op_collection_id ftethz
language English
description Accurate knowledge of snow depth distributions in mountain catchments is critical for applications in hydrology and ecology. Recently, a method was proposed to map snow depth at meter-scale resolution from very-high-resolution stereo satellite imagery (e.g., Pléiades) with an accuracy close to 0.5 m. However, the validation was limited to probe measurements and unmanned aircraft vehicle (UAV) photogrammetry, which sampled a limited fraction of the topographic and snow depth variability. We improve upon this evaluation using accurate maps of the snow depth derived from Airborne Snow Observatory laser-scanning measurements in the Tuolumne river basin, USA. We find a good agreement between both datasets over a snow-covered area of 138 km2 on a 3 m grid, with a positive bias for a Pléiades snow depth of 0.08 m, a root mean square error of 0.80 m and a normalized median absolute deviation (NMAD) of 0.69 m. Satellite data capture the relationship between snow depth and elevation at the catchment scale and also small-scale features like snow drifts and avalanche deposits at a typical scale of tens of meters. The random error at the pixel level is lower in snow-free areas than in snow-covered areas, but it is reduced by a factor of 2 (NMAD of approximately 0.40 m for snow depth) when averaged to a 36 m grid. We conclude that satellite photogrammetry stands out as a convenient method to estimate the spatial distribution of snow depth in high mountain catchments. ISSN:1994-0416 ISSN:1994-0424
format Article in Journal/Newspaper
author Deschamps-Berger, César
Gascoin, Simon
Berthier, Etienne
Deems, Jeffrey
Gutmann, Ethan
Dehecq, Amaury
Shean, David
Dumont, Marie
spellingShingle Deschamps-Berger, César
Gascoin, Simon
Berthier, Etienne
Deems, Jeffrey
Gutmann, Ethan
Dehecq, Amaury
Shean, David
Dumont, Marie
Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data
author_facet Deschamps-Berger, César
Gascoin, Simon
Berthier, Etienne
Deems, Jeffrey
Gutmann, Ethan
Dehecq, Amaury
Shean, David
Dumont, Marie
author_sort Deschamps-Berger, César
title Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data
title_short Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data
title_full Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data
title_fullStr Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data
title_full_unstemmed Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data
title_sort snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data
publisher Copernicus
publishDate 2020
url https://hdl.handle.net/20.500.11850/444952
https://doi.org/10.3929/ethz-b-000444952
genre The Cryosphere
genre_facet The Cryosphere
op_source The Cryosphere, 14 (9)
op_relation info:eu-repo/semantics/altIdentifier/doi/10.5194/tc-14-2925-2020
info:eu-repo/semantics/altIdentifier/wos/000571465800001
http://hdl.handle.net/20.500.11850/444952
doi:10.3929/ethz-b-000444952
op_rights info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International
op_rightsnorm CC-BY
op_doi https://doi.org/20.500.11850/444952
https://doi.org/10.3929/ethz-b-000444952
https://doi.org/10.5194/tc-14-2925-2020
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