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Near-Real Time Automatic Snow Avalanche Activity Monitoring System Using Sentinel-1 SAR Data in Norway

Earth Observation Group, NORCE—Norwegian Research Centre, 9019 Tromsø, Norway
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(23), 2863;
Received: 28 October 2019 / Revised: 22 November 2019 / Accepted: 25 November 2019 / Published: 2 December 2019
Knowledge of the spatio-temporal occurrence of avalanche activity is critical for avalanche forecasting. We present a near-real time automatic avalanche monitoring system that outputs detected avalanche polygons within roughly 10 min after Sentinel-1 SAR data are download. Our avalanche detection algorithm has an average probability of detection (POD) of 67.2% with a false alarm rate (FAR) averaging 45.9, with a maximum POD of over 85% and a minimum FAR of 24.9% compared to manual detection of avalanches. The high variability in performance stems from the dynamic nature of snow in the Sentinel-1 data. After tuning parameters of the detection algorithm, we processed five years of Sentinel-1 images acquired over a 150 × 100 km large area in Northern Norway, with the best setup. Compared to a dataset of field-observed avalanches, 77.3% were manually detectable. Using these manual detections as benchmark, the avalanche detection algorithm achieved an accuracy of 79% with high POD in cases of medium to large wet snow avalanches. For the first time, we present a dataset of spatio-temporal avalanche activity over several winters from a large region. Currently, the Norwegian Avalanche Warning Service is using our processing system for pre-operational use in three regions in Norway. View Full-Text
Keywords: SAR; Sentinel-1; snow avalanche; automatic detection SAR; Sentinel-1; snow avalanche; automatic detection
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MDPI and ACS Style

Eckerstorfer, M.; Vickers, H.; Malnes, E.; Grahn, J. Near-Real Time Automatic Snow Avalanche Activity Monitoring System Using Sentinel-1 SAR Data in Norway. Remote Sens. 2019, 11, 2863.

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