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 (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.

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Publication Details

Journal
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Published
2024-12-27
DOI
https://doi.org/10.1109/jstars.2024.3521612
Citations
3
Primary Topic
Aerospace Engineering and Energy Systems
Type
article
Field-Weighted Citation Impact
3.90
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article

Mixed Analytical-Numerical Modeling of Radar Backscattering for Seasonal Snowpacks

Martina Lodigiani, Marco Pasian, Carlo Marín
3 citations
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Aerospace Engineering and Energy Systems
3.90
article

Mixed Analytical-Numerical Modeling of Radar Backscattering for Seasonal Snowpacks

Martina Lodigiani, Marco Pasian, Carlo Marín
article en
3 citations

Abstract

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.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingVol. 18
Eurac Research (IT), University of Pavia (IT)
Climate action
Openalex Percentile: Top 6%
Aerospace Engineering and Energy Systems
3.90
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Mixed Analytical-Numerical Modeling of Radar Backscattering for Seasonal Snowpacks — Martina Lodigiani, Marco Pasian, et al. · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024) | TGRS Research Map | TGRS