Snow Avalanche Detection and Mapping in single, multitemporal, and multiorbital Radar Images from TerraSAR-X and Sentinel-1

Abstract

Abstract. Snow avalanches can endanger people and infrastructure, especially in densely populated mountainous regions. In Switzerland, the public is informed by an avalanche bulletin issued twice a day during winter which is based on weather information and snow and avalanches reports from a network of observers. During bad weather, however, information about occurred avalanches can be scarce or even be missing completely. To asses the potential of weather independent radar satellites we compared manual and automatic avalanche mapping results from high resolution TerraSAR-X (TSX) stripmap images and from medium resolution Sentinel-1 (S1) interferometric wide swath images. Within a selected test site in the central Swiss Alps the TSX results were also compared to available mapping results from high-resolution SPOT-6 optical satellite images. We found that avalanche outlines from TSX and S1 agree well with each other but with TSX about 40 % more, mainly smaller avalanches were detected. However, S1 provides a much higher spatial and temporal coverage and allows for mapping of the entire Alps at least every 6 days with freely available acquisitions. With costly SPOT-6 images the Alps can be even covered in a single day at meter-resolution, at least for clear sky conditions. For the SPOT-6 and TSX mapping results we found a fair agreement but the temporal information from radar change detection allows for a better separation of overlapping avalanches. Still, with radar, mainly the avalanche deposition zone was detected, whereas the release zone was well visible already in SPOT-6 data. With automatic avalanche mapping we detected around 70 % of the manually mapped new avalanches in the same image pair, at least when the number of old avalanches is low. To further improve the radar mapping capabilities, we combined S1 images from multiple orbits and polarizations and obtained a notable enhancement of resolution and speckle reduction such that the obtained mapping results are almost comparable to the single orbit TSX change detection results. In a multiorbital S1 moasic covering entire Switzerland, we detected 7361 new avalanches which occurred during an extreme avalanche period around Jan 4th 2018.

Mapping avalanches with satellites – evaluation of performance and completeness

“…Sentinel-1 For processing, we followed the steps described in Leinss et al (2020) but added local resolution weighting (LRW; Small, 2012) to optimize the spatial resolution and to minimize terrain shadow and layover effects. For LRW, two acquisitions from orbits with opposite view directions (ascending looking east and descending looking west) were combined using a weighted average based on the local, terrain dependent resolution of every pixel.…”

“…Radar sensors can detect the increased roughness of the snow surface caused by avalanches Malnes, 2015, Leinss et al 2020). Radar satellites, like RadarSat, TerraSAR-X, and Sentinel-1, have been successfully applied for avalanche mapping in various regions (Eckerstorfer and Malnes, 2015;Vickers et al, 2016;Eckerstorfer et al, 2017;Wesselink et al, 2017;Abermann et al, 2019;Leinss et al, 2020). Selective verification has shown that radar underestimates the avalanche activity to an unknown extent (Eckerstorfer et al, 2017).…”

“…Selective verification has shown that radar underestimates the avalanche activity to an unknown extent (Eckerstorfer et al, 2017). Often only parts of the avalanches are mapped, and Sentinel-1 misses most small avalanches due to the limited spatial resolution (Leinss et al, 2020).…”

“…CC BY 4.0 License. Eckerstorfer et al, 2015) and combinations of manual and automatic mapping (Leinss et al, 2020) have been used.…”

“…To do so, we assess the completeness of visually detected and manually mapped avalanches, using three different sensors, which have recently been used to detect avalanches (e.g. Eckerstorfer and Malnes, 2015;Leinss et al, 2020;Bühler et al, 2019;Nolting et al, 2018;Abermann et al, 2019):…”