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

Abstract

Snow avalanches cause significant loss of life and infrastructure in snow covered mountain areas worldwide. Our understanding and ability to forecast avalanche activity in space and time, are limited by incomplete avalanche activity datasets, derived from point-scale field observations. Here we propose the use of C-band synthetic aperture radar (SAR) in detecting avalanche debris. We use high-resolution Radarsat-2 Ultrafine (RS-2U) imagery to manually detect avalanche debris-like features based on the backscatter contrast between avalanche debris and the surrounding, undisturbed snowpack. During March 2014, we acquired 12 RS-2U images, covering roughly 12% of the county of Troms in Northern Norway. Using single backscatter images, we detected 546 avalanche debris-like features of which 57 overlapped in multiple times, 7 were either radar shadows and layovers or natural features, and 15 were eliminated by a topographic GIS model, distinguishing avalanche from non-avalanche terrain. The remaining 467 features were classified as avalanche debris, of which 173 features (37%) could be validated. Validation was carried out in the field, by using optical remote sensing data from Landsat-8, by compiling SAR change detection images and by independent manual expert detection. SAR change detection utilizes the relative backscatter increase of avalanche debris between a snow-free SAR image and a current SAR image with avalanche activity. This relative backscatter increase was quantified with a median relative backscatter of 3.7dB, and a threshold of 1.5dB. In this study, we showed that detection of small sized avalanche debris is possible using RS-2U images. However, the operational usage is limited by the high acquisition costs, small ground swath, and uncertain data availability.