Snow depth derived from Sentinel-1 compared to in-situ observations in northern Finland

Seasonal snow in the northern regions plays an important role providing water resources for both consumption and hydropower generation. Moreover, the snow changes in northern Finland during winter impact the local agriculture, vegetation, tourism and recreational activities. In this study we estimat...

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Main Authors: Lemos, Adriano, Riihelä, Aku
Format: Text
Language:English
Published: 2024
Subjects:
Online Access:https://doi.org/10.5194/egusphere-2024-869
https://egusphere.copernicus.org/preprints/2024/egusphere-2024-869/
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spelling ftcopernicus:oai:publications.copernicus.org:egusphere118979 2024-06-23T07:54:09+00:00 Snow depth derived from Sentinel-1 compared to in-situ observations in northern Finland Lemos, Adriano Riihelä, Aku 2024-05-13 application/pdf https://doi.org/10.5194/egusphere-2024-869 https://egusphere.copernicus.org/preprints/2024/egusphere-2024-869/ eng eng doi:10.5194/egusphere-2024-869 https://egusphere.copernicus.org/preprints/2024/egusphere-2024-869/ eISSN: Text 2024 ftcopernicus https://doi.org/10.5194/egusphere-2024-869 2024-06-13T01:24:45Z Seasonal snow in the northern regions plays an important role providing water resources for both consumption and hydropower generation. Moreover, the snow changes in northern Finland during winter impact the local agriculture, vegetation, tourism and recreational activities. In this study we estimated snow depth using an empirical methodology applied to the dual-polarisation of the Sentinel-1 synthetic aperture radar (SAR) images and compared with in situ measurements collected by automatic weather stations (AWS) in northern Finland. We applied an adapted version of the empirical methodology developed by Lievens et al. (2019) to retrieve snow depth, using Sentinel-1 constellation between 2019 and 2022, and then compared to measurements from three automatic weather stations available over the same period. Overall, the Sentinel-1 snow depth retrievals were underestimated in comparison with the in-situ measurements from the automatic weather stations. We found slightly different patterns for the different years, and an overall correlation factor of 0.41, and a higher correlation in the 2020–2021 season (R=0.52). The high correlation between estimated and measured snow depth at the Inari Nellim location (R=0.81) reinforces the potential ability to derive snow changes in regions where in situ measurements of snow are currently lacking. Further investigation is still necessary to better understand how the physical properties of the snowpack influence the backscatter response over shallow snow regions. Text Inari Northern Finland Copernicus Publications: E-Journals Inari ENVELOPE(27.029,27.029,68.906,68.906) Nellim ENVELOPE(28.306,28.306,68.847,68.847) The Sentinel ENVELOPE(73.317,73.317,-52.983,-52.983)
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description Seasonal snow in the northern regions plays an important role providing water resources for both consumption and hydropower generation. Moreover, the snow changes in northern Finland during winter impact the local agriculture, vegetation, tourism and recreational activities. In this study we estimated snow depth using an empirical methodology applied to the dual-polarisation of the Sentinel-1 synthetic aperture radar (SAR) images and compared with in situ measurements collected by automatic weather stations (AWS) in northern Finland. We applied an adapted version of the empirical methodology developed by Lievens et al. (2019) to retrieve snow depth, using Sentinel-1 constellation between 2019 and 2022, and then compared to measurements from three automatic weather stations available over the same period. Overall, the Sentinel-1 snow depth retrievals were underestimated in comparison with the in-situ measurements from the automatic weather stations. We found slightly different patterns for the different years, and an overall correlation factor of 0.41, and a higher correlation in the 2020–2021 season (R=0.52). The high correlation between estimated and measured snow depth at the Inari Nellim location (R=0.81) reinforces the potential ability to derive snow changes in regions where in situ measurements of snow are currently lacking. Further investigation is still necessary to better understand how the physical properties of the snowpack influence the backscatter response over shallow snow regions.
format Text
author Lemos, Adriano
Riihelä, Aku
spellingShingle Lemos, Adriano
Riihelä, Aku
Snow depth derived from Sentinel-1 compared to in-situ observations in northern Finland
author_facet Lemos, Adriano
Riihelä, Aku
author_sort Lemos, Adriano
title Snow depth derived from Sentinel-1 compared to in-situ observations in northern Finland
title_short Snow depth derived from Sentinel-1 compared to in-situ observations in northern Finland
title_full Snow depth derived from Sentinel-1 compared to in-situ observations in northern Finland
title_fullStr Snow depth derived from Sentinel-1 compared to in-situ observations in northern Finland
title_full_unstemmed Snow depth derived from Sentinel-1 compared to in-situ observations in northern Finland
title_sort snow depth derived from sentinel-1 compared to in-situ observations in northern finland
publishDate 2024
url https://doi.org/10.5194/egusphere-2024-869
https://egusphere.copernicus.org/preprints/2024/egusphere-2024-869/
long_lat ENVELOPE(27.029,27.029,68.906,68.906)
ENVELOPE(28.306,28.306,68.847,68.847)
ENVELOPE(73.317,73.317,-52.983,-52.983)
geographic Inari
Nellim
The Sentinel
geographic_facet Inari
Nellim
The Sentinel
genre Inari
Northern Finland
genre_facet Inari
Northern Finland
op_source eISSN:
op_relation doi:10.5194/egusphere-2024-869
https://egusphere.copernicus.org/preprints/2024/egusphere-2024-869/
op_doi https://doi.org/10.5194/egusphere-2024-869
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