X- and Ku-Band SAR Backscattering Signatures of Snow-Covered Lake Ice and Sea Ice
Funding Information: This research was partly funded by ESA SnowSAR Campaign Data Analysis Study (SCADAS); ESA Contract No. 4000118400/16/NL/FF/gp. Publisher Copyright: © 2024 by the authors. In this work, backscattering signatures of snow-covered lake ice and sea ice from X- and Ku-band synthetic a...
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Online Access: | https://aaltodoc.aalto.fi/handle/123456789/126684 https://doi.org/10.3390/rs16020369 |
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ftaaltouniv:oai:aaltodoc.aalto.fi:123456789/126684 2024-04-28T08:32:26+00:00 X- and Ku-Band SAR Backscattering Signatures of Snow-Covered Lake Ice and Sea Ice Veijola, Katriina Cohen, Juval Mäkynen, Marko Lemmetyinen, Juha Praks, Jaan Cheng, Bin Department of Electronics and Nanoengineering Jaan Praks Group Finnish Meteorological Institute Aalto-yliopisto Aalto University 2024-01 application/pdf https://aaltodoc.aalto.fi/handle/123456789/126684 https://doi.org/10.3390/rs16020369 en eng MDPI AG Remote Sensing Volume 16, issue 2 Veijola, K, Cohen, J, Mäkynen, M, Lemmetyinen, J, Praks, J & Cheng, B 2024, ' X- and Ku-Band SAR Backscattering Signatures of Snow-Covered Lake Ice and Sea Ice ', Remote Sensing, vol. 16, no. 2, 369 . https://doi.org/10.3390/rs16020369 2072-4292 PURE UUID: 304ba8a2-8fe6-4988-9a60-ede9f8cc4d15 PURE ITEMURL: https://research.aalto.fi/en/publications/304ba8a2-8fe6-4988-9a60-ede9f8cc4d15 PURE LINK: http://www.scopus.com/inward/record.url?scp=85183318493&partnerID=8YFLogxK PURE FILEURL: https://research.aalto.fi/files/135876955/Veijola_X-and-ku-band-SAR_backscattering_remotesensing-16-00369-v2.pdf https://aaltodoc.aalto.fi/handle/123456789/126684 URN:NBN:fi:aalto-202402072343 doi:10.3390/rs16020369 openAccess remote sensing sea ice snow synthetic aperture radar A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä publishedVersion 2024 ftaaltouniv https://doi.org/10.3390/rs16020369 2024-04-10T00:21:31Z Funding Information: This research was partly funded by ESA SnowSAR Campaign Data Analysis Study (SCADAS); ESA Contract No. 4000118400/16/NL/FF/gp. Publisher Copyright: © 2024 by the authors. In this work, backscattering signatures of snow-covered lake ice and sea ice from X- and Ku-band synthetic aperture radar (SAR) data are investigated. The SAR data were acquired with the ESA airborne SnowSAR sensor in winter 2012 over Lake Orajärvi in northern Finland and over landfast ice in the Bay of Bothnia of the Baltic Sea. Co-incident with the SnowSAR acquisitions, in situ snow and ice data were measured. In addition, time series of TerraSAR-X images and ice mass balance buoy data were acquired for Lake Orajärvi in 2011–2012. The main objective of our study was to investigate relationships between SAR backscattering signatures and snow depth over lake and sea ice, with the ultimate objective of assessing the feasibility of retrieval of snow characteristics using X- and Ku-band dual-polarization (VV and VH) SAR over freshwater or sea ice. This study constitutes the first comprehensive survey of snow backscattering signatures at these two combined frequencies over both lake and sea ice. For lake ice, we show that X-band VH-polarized backscattering coefficient ((Formula presented.)) and the Ku-band VV/VH-ratio exhibited the highest sensitivity to the snow depth. For sea ice, the highest sensitivity to the snow depth was found from the Ku-band VV-polarized (Formula presented.) and the Ku-band VV/VH-ratio. However, the observed relations were relatively weak, indicating that at least for the prevailing snow conditions, obtaining reliable estimates of snow depth over lake and sea ice would be challenging using only X- and Ku-band backscattering information. Peer reviewed Article in Journal/Newspaper Northern Finland Sea ice Aalto University Publication Archive (Aaltodoc) Remote Sensing 16 2 369 |
institution |
Open Polar |
collection |
Aalto University Publication Archive (Aaltodoc) |
op_collection_id |
ftaaltouniv |
language |
English |
topic |
remote sensing sea ice snow synthetic aperture radar |
spellingShingle |
remote sensing sea ice snow synthetic aperture radar Veijola, Katriina Cohen, Juval Mäkynen, Marko Lemmetyinen, Juha Praks, Jaan Cheng, Bin X- and Ku-Band SAR Backscattering Signatures of Snow-Covered Lake Ice and Sea Ice |
topic_facet |
remote sensing sea ice snow synthetic aperture radar |
description |
Funding Information: This research was partly funded by ESA SnowSAR Campaign Data Analysis Study (SCADAS); ESA Contract No. 4000118400/16/NL/FF/gp. Publisher Copyright: © 2024 by the authors. In this work, backscattering signatures of snow-covered lake ice and sea ice from X- and Ku-band synthetic aperture radar (SAR) data are investigated. The SAR data were acquired with the ESA airborne SnowSAR sensor in winter 2012 over Lake Orajärvi in northern Finland and over landfast ice in the Bay of Bothnia of the Baltic Sea. Co-incident with the SnowSAR acquisitions, in situ snow and ice data were measured. In addition, time series of TerraSAR-X images and ice mass balance buoy data were acquired for Lake Orajärvi in 2011–2012. The main objective of our study was to investigate relationships between SAR backscattering signatures and snow depth over lake and sea ice, with the ultimate objective of assessing the feasibility of retrieval of snow characteristics using X- and Ku-band dual-polarization (VV and VH) SAR over freshwater or sea ice. This study constitutes the first comprehensive survey of snow backscattering signatures at these two combined frequencies over both lake and sea ice. For lake ice, we show that X-band VH-polarized backscattering coefficient ((Formula presented.)) and the Ku-band VV/VH-ratio exhibited the highest sensitivity to the snow depth. For sea ice, the highest sensitivity to the snow depth was found from the Ku-band VV-polarized (Formula presented.) and the Ku-band VV/VH-ratio. However, the observed relations were relatively weak, indicating that at least for the prevailing snow conditions, obtaining reliable estimates of snow depth over lake and sea ice would be challenging using only X- and Ku-band backscattering information. Peer reviewed |
author2 |
Department of Electronics and Nanoengineering Jaan Praks Group Finnish Meteorological Institute Aalto-yliopisto Aalto University |
format |
Article in Journal/Newspaper |
author |
Veijola, Katriina Cohen, Juval Mäkynen, Marko Lemmetyinen, Juha Praks, Jaan Cheng, Bin |
author_facet |
Veijola, Katriina Cohen, Juval Mäkynen, Marko Lemmetyinen, Juha Praks, Jaan Cheng, Bin |
author_sort |
Veijola, Katriina |
title |
X- and Ku-Band SAR Backscattering Signatures of Snow-Covered Lake Ice and Sea Ice |
title_short |
X- and Ku-Band SAR Backscattering Signatures of Snow-Covered Lake Ice and Sea Ice |
title_full |
X- and Ku-Band SAR Backscattering Signatures of Snow-Covered Lake Ice and Sea Ice |
title_fullStr |
X- and Ku-Band SAR Backscattering Signatures of Snow-Covered Lake Ice and Sea Ice |
title_full_unstemmed |
X- and Ku-Band SAR Backscattering Signatures of Snow-Covered Lake Ice and Sea Ice |
title_sort |
x- and ku-band sar backscattering signatures of snow-covered lake ice and sea ice |
publisher |
MDPI AG |
publishDate |
2024 |
url |
https://aaltodoc.aalto.fi/handle/123456789/126684 https://doi.org/10.3390/rs16020369 |
genre |
Northern Finland Sea ice |
genre_facet |
Northern Finland Sea ice |
op_relation |
Remote Sensing Volume 16, issue 2 Veijola, K, Cohen, J, Mäkynen, M, Lemmetyinen, J, Praks, J & Cheng, B 2024, ' X- and Ku-Band SAR Backscattering Signatures of Snow-Covered Lake Ice and Sea Ice ', Remote Sensing, vol. 16, no. 2, 369 . https://doi.org/10.3390/rs16020369 2072-4292 PURE UUID: 304ba8a2-8fe6-4988-9a60-ede9f8cc4d15 PURE ITEMURL: https://research.aalto.fi/en/publications/304ba8a2-8fe6-4988-9a60-ede9f8cc4d15 PURE LINK: http://www.scopus.com/inward/record.url?scp=85183318493&partnerID=8YFLogxK PURE FILEURL: https://research.aalto.fi/files/135876955/Veijola_X-and-ku-band-SAR_backscattering_remotesensing-16-00369-v2.pdf https://aaltodoc.aalto.fi/handle/123456789/126684 URN:NBN:fi:aalto-202402072343 doi:10.3390/rs16020369 |
op_rights |
openAccess |
op_doi |
https://doi.org/10.3390/rs16020369 |
container_title |
Remote Sensing |
container_volume |
16 |
container_issue |
2 |
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369 |
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1797589632407306240 |