Monitoring snow avalanches from SAR data with deep learning

TL;DR

This paper explores the use of deep learning techniques to detect and segment snow avalanches from SAR satellite data, demonstrating improved accuracy and large-scale monitoring capabilities in mountainous regions.

Contribution

It introduces advanced deep learning models for pixel-level avalanche segmentation from SAR data and applies them to large-scale detection across Norway.

Findings

Deep learning models outperform traditional methods in avalanche detection.

Pixel-level segmentation improves spatial accuracy.

Large-scale application reveals spatial and temporal avalanche patterns.

Abstract

Snow avalanches present significant risks to human life and infrastructure, particularly in mountainous regions, making effective monitoring crucial. Traditional monitoring methods, such as field observations, are limited by accessibility, weather conditions, and cost. Satellite-borne Synthetic Aperture Radar (SAR) data has become an important tool for large-scale avalanche detection, as it can capture data in all weather conditions and across remote areas. However, traditional processing methods struggle with the complexity and variability of avalanches. This chapter reviews the application of deep learning for detecting and segmenting snow avalanches from SAR data. Early efforts focused on the binary classification of SAR images, while recent advances have enabled pixel-level segmentation, providing greater accuracy and spatial resolution. A case study using Sentinel-1 SAR data demonstrates the effectiveness of deep learning models for avalanche segmentation, achieving superior results over traditional methods. We also present an extension of this work, testing recent state-of-the-art segmentation architectures on an expanded dataset of over 4,500 annotated SAR images. The best-performing model among those tested was applied for large-scale avalanche detection across the whole of Norway, revealing important spatial and temporal patterns over several winter seasons.