Manual detection of snow avalanche debris using high-resolution Radarsat-2 SAR images

Eckerstorfer, Markus; Malnes, Eirik

doi:10.1016/j.coldregions.2015.08.016

Cited by 44 publications

(63 citation statements)

References 27 publications

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“…Avalanche detection in SAR images has been introduced by Wiesmann et al [8] using ERS-1 and ERS-2 C-band SAR data. Subsequent studies experimented with X-band TerraSAR-X data [9] and C-band Radarsat-2 Ultrafine mode data [10]. In follow-up studies, C-band SAR data provided by Sentinel-1 were used.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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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.

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Section: Introductionmentioning

confidence: 99%

“…In follow-up studies, C-band SAR data provided by Sentinel-1 were used. [10,11]. Common for these studies, avalanches were detected by expert interpretation of temporal change detection images over time series of up to one winter.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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“…Radar satellites have the advantage of acquiring data despite clouds and without daylight. Therefore, radar data has also been applied to generate avalanche maps (Eckerstorfer and Malnes, 2015;Vickers et al, 2016;Eckerstorfer et al, 40 2017;Wesselink et al, 2017). Due to the coarser spatial resolution (3 -30 m) and limitations by the observation geometries (radar shadow and layover), considerable parts of mountain regions cannot be covered.…”

Section: Introduction 30mentioning

confidence: 99%

Where are the avalanches? Rapid mapping of a large snow avalanche period with optical satellites

Bühler¹,

Hafner²,

Zweifel³

et al. 2019

Preprint

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Accurate and timely information on avalanche occurrence are key for avalanche warning, crisis 10 management and avalanche documentation. Today such information is mainly available at isolated locations provided by observers in the field. The achieved reliability considering accuracy, completeness and reliability of the reported avalanche events is limited. In this study we present the spatial continuous mapping of a large avalanche period in January 2018 covering the majority of the Swiss Alps (12'500 km 2 ). 15We tested different satellite sensors available for rapid mapping during a first avalanche period. Based on these experiences, we tasked SPOT6/7 data for data acquisition to cover the second, much larger avalanche period. We manually mapped the outlines of 18'737 individual avalanche events, applying image enhancement techniques to analyze regions in cast shadow as well as brightly illuminated ones. 20The resulting dataset of mapped avalanche outlines, having a unique completeness and reliability, is evaluated to produce maps of avalanche occurrence and avalanche size. We validated the mapping of the avalanche outlines using photographs acquired from helicopters just after the avalanche period.This study demonstrates the applicability of optical, very high spatial resolution satellite data to map an 25 exceptional avalanche period with very high completeness, accuracy and reliability over a large region.

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“…Recent studies by Malnes et al [2013], Bühler et al [2014], and Eckerstorfer and Malnes [2015] have made use of change detection methods in order to detect avalanche debris. This technique identifies the temporal change in radar backscatter between two SAR scenes acquired, one from before avalanche activity has taken place and another from after.…”

Section: Introductionmentioning

confidence: 99%

A method for automated snow avalanche debris detection through use of synthetic aperture radar (SAR) imaging

Vickers

Eckerstorfer

Malnes

et al. 2016

Earth and Space Science

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Avalanches are a natural hazard that occur in mountainous regions of Troms County in northern Norway during winter and can cause loss of human life and damage to infrastructure. Knowledge of when and where they occur especially in remote, high mountain areas is often lacking due to difficult access. However, complete, spatiotemporal avalanche activity data sets are important for accurate avalanche forecasting, as well as for deeper understanding of the link between avalanche occurrences and the triggering snowpack and meteorological factors. It is therefore desirable to develop a technique that enables active mapping and monitoring of avalanches over an entire winter. Avalanche debris can be observed remotely over large spatial areas, under all weather and light conditions by synthetic aperture radar (SAR) satellites. The recently launched Sentinel-1A satellite acquires SAR images covering the entire Troms County with frequent updates. By focusing on a case study from New Year 2015 we use Sentinel-1A images to develop an automated avalanche debris detection algorithm that utilizes change detection and unsupervised object classification methods. We compare our results with manually identified avalanche debris and field-based images to quantify the algorithm accuracy. Our results indicate that a correct detection rate of over 60% can be achieved, which is sensitive to several algorithm parameters that may need revising. With further development and refinement of the algorithm, we believe that this method could play an effective role in future operational monitoring of avalanches within Troms and has potential application in avalanche forecasting areas worldwide.

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Manual detection of snow avalanche debris using high-resolution Radarsat-2 SAR images

Cited by 44 publications

References 27 publications

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

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

Where are the avalanches? Rapid mapping of a large snow avalanche period with optical satellites

A method for automated snow avalanche debris detection through use of synthetic aperture radar (SAR) imaging

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