Mixed Analytical-Numerical Modeling of Radar Backscattering for Seasonal Snowpacks
The intensity of the backscattered signal collected by active radars over wet, seasonal snowpacks depends on numerous variables related to the snowpack, which are often difficult to determine accurately. In recent years, thanks to the increased availability of spaceborne synthetic aperture radars (S...
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IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10817100/ |
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| author | Martina Lodigiani Carlo Marin Marco Pasian |
| author_facet | Martina Lodigiani Carlo Marin Marco Pasian |
| author_sort | Martina Lodigiani |
| collection | DOAJ |
| description | The intensity of the backscattered signal collected by active radars over wet, seasonal snowpacks depends on numerous variables related to the snowpack, which are often difficult to determine accurately. In recent years, thanks to the increased availability of spaceborne synthetic aperture radars (SARs), a temporal relationship between wet-snow metamorphism and microwave backscattering has been demonstrated. However, a precise quantitative description of this phenomenon has yet to be fully determined. In this article, we propose a new mixed analytical-numerical model to describe the effect of the physical parameters related to the wet snowpack metamorphism on the intensity of the backscattering at L, C, and X bands, with a focus on high alpine snowpacks. Particular attention was paid to integrate the effects of the snow superficial roughness and the snow scattering. The model is first applied to several simulated snowpacks and then validated against a real multitemporal SAR signature acquired by Sentinel-1 over the snow station of Malga Fadner (South Tyrol, Italy) and of Torgnon (Aosta Valley, Italy). The comparison between the model outcomes and the satellite data were in good agreement, leading to the possibility of using such method for operational identification of the run-off phase from remote locations. |
| format | Article |
| id | doaj-art-1e4faf1ab83247e1a3db4e8225a2939e |
| institution | Kabale University |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-1e4faf1ab83247e1a3db4e8225a2939e2025-01-30T00:00:11ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-01183461347110.1109/JSTARS.2024.352161210817100Mixed Analytical-Numerical Modeling of Radar Backscattering for Seasonal SnowpacksMartina Lodigiani0https://orcid.org/0000-0003-1703-1375Carlo Marin1https://orcid.org/0000-0001-6987-9445Marco Pasian2https://orcid.org/0000-0003-3530-7419Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, ItalyInstitute for Earth Observation, Eurac Research, Bolzano, ItalyDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, ItalyThe intensity of the backscattered signal collected by active radars over wet, seasonal snowpacks depends on numerous variables related to the snowpack, which are often difficult to determine accurately. In recent years, thanks to the increased availability of spaceborne synthetic aperture radars (SARs), a temporal relationship between wet-snow metamorphism and microwave backscattering has been demonstrated. However, a precise quantitative description of this phenomenon has yet to be fully determined. In this article, we propose a new mixed analytical-numerical model to describe the effect of the physical parameters related to the wet snowpack metamorphism on the intensity of the backscattering at L, C, and X bands, with a focus on high alpine snowpacks. Particular attention was paid to integrate the effects of the snow superficial roughness and the snow scattering. The model is first applied to several simulated snowpacks and then validated against a real multitemporal SAR signature acquired by Sentinel-1 over the snow station of Malga Fadner (South Tyrol, Italy) and of Torgnon (Aosta Valley, Italy). The comparison between the model outcomes and the satellite data were in good agreement, leading to the possibility of using such method for operational identification of the run-off phase from remote locations.https://ieeexplore.ieee.org/document/10817100/Electromagnetic (EM) modelmelting cyclemicrowave radarseasonal snowSentinel-1snowpack |
| spellingShingle | Martina Lodigiani Carlo Marin Marco Pasian Mixed Analytical-Numerical Modeling of Radar Backscattering for Seasonal Snowpacks IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Electromagnetic (EM) model melting cycle microwave radar seasonal snow Sentinel-1 snowpack |
| title | Mixed Analytical-Numerical Modeling of Radar Backscattering for Seasonal Snowpacks |
| title_full | Mixed Analytical-Numerical Modeling of Radar Backscattering for Seasonal Snowpacks |
| title_fullStr | Mixed Analytical-Numerical Modeling of Radar Backscattering for Seasonal Snowpacks |
| title_full_unstemmed | Mixed Analytical-Numerical Modeling of Radar Backscattering for Seasonal Snowpacks |
| title_short | Mixed Analytical-Numerical Modeling of Radar Backscattering for Seasonal Snowpacks |
| title_sort | mixed analytical numerical modeling of radar backscattering for seasonal snowpacks |
| topic | Electromagnetic (EM) model melting cycle microwave radar seasonal snow Sentinel-1 snowpack |
| url | https://ieeexplore.ieee.org/document/10817100/ |
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