Item: SAR REMOTE SENSING AS A SUPPORT TOOL FOR OPERATIONAL AVALANCHE FORECASTING
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Title: SAR REMOTE SENSING AS A SUPPORT TOOL FOR OPERATIONAL AVALANCHE FORECASTING
Proceedings: Proceedings, International Snow Science Workshop, Whistler, BC, Canada, 2026
Authors:
- Alberto Mariani [ University of Insubria, Como, Italy ] [ Alpsolut S.r.l., Livigno, Italy ]
- Jacopo Borsotti [ Simon Fraser University, Burnaby, BC, Canada ]
- Martin Metzger [ Alpsolut S.r.l., Livigno, Italy ]
- Giacomo Villa [ Alpsolut S.r.l., Livigno, Italy ]
- Luca Dellarole [ Alpsolut S.r.l., Livigno, Italy ]
- Martin Ahrland Stefan [ Wyssen Avalanche Control, Tromsø, Norway ]
- Franz Livio [ University of Insubria, Como, Italy ]
- Fabiano Monti [ Alpsolut S.r.l., Livigno, Italy ]
Date: 2026-09-28
Abstract: Synthetic Aperture Radar (SAR) remote sensing has increasingly been exploited for snow and avalanche research to derive spatially explicit information. For example, models have been developed to detect wet snow, measure snow depth, and reconstruct avalanche activity by identifying avalanche deposits. These models have demonstrated their effectiveness in retrieving snow cover information over time, allowing the derivation of valuable historical records for specific regions. Such information is crucial for avalanche-related land-use planning, which relies on the occurrence and extent of past extreme avalanche events. It also supports the development of reference datasets to validate and improve snowpack and avalanche hazard modelling approaches. However, the role of SAR in operational avalanche forecasting remains less straightforward, as SAR data are typically collected at multi-day intervals and primarily provide information on current or past conditions, whereas public avalanche forecasts are issued daily to support short-term forecasting. This temporal mismatch raises an important question: how can SAR data meaningfully contribute to operational avalanche forecasting? In this study, we address this question from the perspective of a forecaster. Rather than viewing SAR as a standalone tool, we frame it as an additional layer of information that can support field observations and the monitoring of snowpack conditions. Using real-case examples from the Livigno Avalanche Center (Italy) and Tromsø (Norway), we show how SAR-derived information can help update or confirm the spatial distribution of key avalanche-relevant features and highlight areas where field evidence is sparse. Specifically, we show how SAR-derived products are translated into the improvement of avalanche forecasting throughout a winter season. Overall, this work argues that the value of SAR for operational avalanche forecasting lies not only in snowpack monitoring, but also in its ability to provide independent, spatially extensive snapshots that can strengthen the forecast process, improve the consistency of public avalanche forecasts, and bridge gaps between field observation and snowpack spatial variability.
Object ID: ISSW2026_O7.6.pdf
DOI: https://doi.org/10.15788/1790098656
Language of Article: English
Presenter(s): Alberto Mariani
Keywords: Synthetic Aperture Radar; remote sensing; wet snow; snow depth; avalanche deposits
Page Number(s): 1143 - 1149
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