Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions

Detailed information on seasonal snow cover and depth is essential to the understanding of snow processes, to operational forecasting, and as input for hydrological models. Recent advances in uncrewed or unmanned aircraft systems (UASs) and structure from motion (SfM) techniques have enabled low-cos...

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Published in:The Cryosphere
Main Authors: Meriö, Leo-Juhani, Rauhala, Anssi, Ala-aho, Pertti, Kuzmin, Anton, Korpelainen, Pasi, Kumpula, Timo, Kløve, Bjørn, Marttila, Hannu
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2023
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Online Access:https://doi.org/10.5194/tc-17-4363-2023
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author Meriö, Leo-Juhani
Rauhala, Anssi
Ala-aho, Pertti
Kuzmin, Anton
Korpelainen, Pasi
Kumpula, Timo
Kløve, Bjørn
Marttila, Hannu
author_facet Meriö, Leo-Juhani
Rauhala, Anssi
Ala-aho, Pertti
Kuzmin, Anton
Korpelainen, Pasi
Kumpula, Timo
Kløve, Bjørn
Marttila, Hannu
author_sort Meriö, Leo-Juhani
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description Detailed information on seasonal snow cover and depth is essential to the understanding of snow processes, to operational forecasting, and as input for hydrological models. Recent advances in uncrewed or unmanned aircraft systems (UASs) and structure from motion (SfM) techniques have enabled low-cost monitoring of spatial snow depth distribution in resolutions of up to a few centimeters. Here, we study the spatiotemporal variability in snow depth and interactions between snow and vegetation in different subarctic landscapes consisting of a mosaic of conifer forest, mixed forest, transitional woodland/shrub, and peatland areas. To determine the spatiotemporal variability in snow depth, we used high-resolution (50 cm) snow depth maps generated from repeated UAS–SfM surveys in the winter of 2018/2019 and a snow-free bare-ground survey after snowmelt. Due to poor subcanopy penetration with the UAS–SfM method, tree masks were utilized to remove canopy areas and the area (36 cm) immediately next to the canopy before analysis. Snow depth maps were compared to the in situ snow course and a single-point continuous ultrasonic snow depth measurement. Based on the results, the difference between the UAS–SfM survey median snow depth and single-point measurement increased for all land cover types during the snow season, from +5 cm at the beginning of the accumulation to −16 cm in coniferous forests and −32 cm in peatland during the melt period. This highlights the poor representation of point measurements in selected locations even on the subcatchment scale. The high-resolution snow depth maps agreed well with the snow course measurement, but the spatial extent and resolution of maps were substantially higher. The snow depth range (5th–95th percentiles) within different land cover types increased from 17 to 42 cm in peatlands and from 33 to 49 cm in the coniferous forest from the beginning of the snow accumulation to the melt period. Both the median snow depth and its range were found to increase with canopy density; this ...
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spelling ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00069355 2025-01-17T01:00:36+00:00 Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions Meriö, Leo-Juhani Rauhala, Anssi Ala-aho, Pertti Kuzmin, Anton Korpelainen, Pasi Kumpula, Timo Kløve, Bjørn Marttila, Hannu 2023-10 electronic https://doi.org/10.5194/tc-17-4363-2023 https://noa.gwlb.de/receive/cop_mods_00069355 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00067742/tc-17-4363-2023.pdf https://tc.copernicus.org/articles/17/4363/2023/tc-17-4363-2023.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-17-4363-2023 https://noa.gwlb.de/receive/cop_mods_00069355 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00067742/tc-17-4363-2023.pdf https://tc.copernicus.org/articles/17/4363/2023/tc-17-4363-2023.pdf https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess article Verlagsveröffentlichung article Text doc-type:article 2023 ftnonlinearchiv https://doi.org/10.5194/tc-17-4363-2023 2023-10-22T23:22:31Z Detailed information on seasonal snow cover and depth is essential to the understanding of snow processes, to operational forecasting, and as input for hydrological models. Recent advances in uncrewed or unmanned aircraft systems (UASs) and structure from motion (SfM) techniques have enabled low-cost monitoring of spatial snow depth distribution in resolutions of up to a few centimeters. Here, we study the spatiotemporal variability in snow depth and interactions between snow and vegetation in different subarctic landscapes consisting of a mosaic of conifer forest, mixed forest, transitional woodland/shrub, and peatland areas. To determine the spatiotemporal variability in snow depth, we used high-resolution (50 cm) snow depth maps generated from repeated UAS–SfM surveys in the winter of 2018/2019 and a snow-free bare-ground survey after snowmelt. Due to poor subcanopy penetration with the UAS–SfM method, tree masks were utilized to remove canopy areas and the area (36 cm) immediately next to the canopy before analysis. Snow depth maps were compared to the in situ snow course and a single-point continuous ultrasonic snow depth measurement. Based on the results, the difference between the UAS–SfM survey median snow depth and single-point measurement increased for all land cover types during the snow season, from +5 cm at the beginning of the accumulation to −16 cm in coniferous forests and −32 cm in peatland during the melt period. This highlights the poor representation of point measurements in selected locations even on the subcatchment scale. The high-resolution snow depth maps agreed well with the snow course measurement, but the spatial extent and resolution of maps were substantially higher. The snow depth range (5th–95th percentiles) within different land cover types increased from 17 to 42 cm in peatlands and from 33 to 49 cm in the coniferous forest from the beginning of the snow accumulation to the melt period. Both the median snow depth and its range were found to increase with canopy density; this ... Article in Journal/Newspaper Subarctic The Cryosphere Niedersächsisches Online-Archiv NOA The Cryosphere 17 10 4363 4380
spellingShingle article
Verlagsveröffentlichung
Meriö, Leo-Juhani
Rauhala, Anssi
Ala-aho, Pertti
Kuzmin, Anton
Korpelainen, Pasi
Kumpula, Timo
Kløve, Bjørn
Marttila, Hannu
Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions
title Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions
title_full Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions
title_fullStr Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions
title_full_unstemmed Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions
title_short Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions
title_sort measuring the spatiotemporal variability in snow depth in subarctic environments using uass – part 2: snow processes and snow–canopy interactions
topic article
Verlagsveröffentlichung
topic_facet article
Verlagsveröffentlichung
url https://doi.org/10.5194/tc-17-4363-2023
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https://tc.copernicus.org/articles/17/4363/2023/tc-17-4363-2023.pdf