Automated snow avalanche release area delineation – validation of existing algorithms and proposition of a new object-based approach for large-scale hazard indication mapping

Abstract

Abstract. Snow avalanche hazard is threatening people and infrastructure in all alpine regions with seasonal or permanent snow cover around the globe. Coping with this hazard is a big challenge and during the past centuries, different strategies were developed. Today, in Switzerland, experienced avalanche engineers produce hazard maps with a very high reliability based on avalanche database information, terrain analysis, climatological data sets and numerical modeling of the flow dynamics for selected avalanche tracks that might affect settlements. However, for regions outside the considered settlement areas such area-wide hazard maps are not available mainly because of the too high cost, in Switzerland and in most mountain regions around the world. Therefore, hazard indication maps, even though they are less reliable and less detailed, are often the only spatial planning tool available. To produce meaningful and cost-effective avalanche hazard indication maps over large regions (regional to national scale), automated release area delineation has to be combined with volume estimations and state-of-the-art numerical avalanche simulations. In this paper we validate existing potential release area (PRA) delineation algorithms, published in peer-reviewed journals, that are based on digital terrain models and their derivatives such as slope angle, aspect, roughness and curvature. For validation, we apply avalanche data from three different ski resorts in the vicinity of Davos, Switzerland, where experienced ski-patrol staff have mapped most avalanches in detail for many years. After calculating the best fit input parameters for every tested algorithm, we compare their performance based on the reference data sets. Because all tested algorithms do not provide meaningful delineation between individual PRAs, we propose a new algorithm based on object-based image analysis (OBIA). In combination with an automatic procedure to estimate the average release depth (d0), defining the avalanche release volume, this algorithm enables the numerical simulation of thousands of avalanches over large regions applying the well-established avalanche dynamics model RAMMS. We demonstrate this for the region of Davos for two hazard scenarios, frequent (10–30-year return period) and extreme (100–300-year return period). This approach opens the door for large-scale avalanche hazard indication mapping in all regions where high-quality and high-resolution digital terrain models and snow data are available.

Spatial Modeling of Snow Avalanche Using Machine Learning Models and Geo-Environmental Factors: Comparison of Effectiveness in Two Mountain Regions

“…Therefore, predicting the zones of this hazard is essential for the reduction of risk (the probability of avalanche occurrence) and for the mitigation of avalanche hazards (the probability of impacts on people and their interests) [10,11]. Different approaches have been employed for producing a snow avalanche susceptibility map (SASM), including multi-criteria decision analysis (MCDA) methods [12][13][14] and fuzzy-frequency ratio models [15][16][17]. However, these methods are expert opinion-based and subjective.…”

“…Some researchers have used numerical methods and dynamic models to analyze the snow avalanche hazard [18][19][20][21], however a lot of uncertainty is involved in all the modeling parameters when applying to large regions at smaller scales. Other research methods are based upon remote-sensing techniques [14,[22][23][24][25]. Though remote sensing can provide useful information about snow surface and land surface conditions, analysis of the complicated relationships between snow avalanches and geomorphometrics has been often ignored.…”

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

“…To further improve the speed of the manual mapping we plan to confine the area that could theoretically be covered by avalanches. Bühler et al (2018) developed an algorithm for large scale hazard indication 10 mapping combining automated release area delineation with numerical avalanche dynamic simulations with RAMMS (Christen et al, 2010). Such a mask could limit the area to investigate considerably saving time and costs.…”

“…Information on the occurrence and runout of snow avalanches is a key parameter for the development of effective hazard mitigation approaches for settlements and traffic infrastructure (Rudolf-Miklau et al, 2014;Bühler et al, 2018). Evidence on the locations and dimensions of avalanches is applied in hazard zone mapping, for the evaluation of protection measures and for the validation and further development of numerical avalanche simulation software such as SAMOS (Sampl and Zwinger, 2004) or RAMMS 35 https://doi.org /10.5194/tc-2019-119 Preprint.…”

Snow avalanche susceptibility of the Circo de Gredos (Iberian Central System, Spain)

“…Therefore, numerous studies following diverse methodologies have addressed the topic, especially in the French and Swiss Alps. So far, significant advances in automated mapping have allowed to assess snow avalanche hazard over large areas by extracting topographic parametres from digital elevation models, which strongly facilitates risk management (Barbolini, Pagliardi, Ferro, & Corradeghini 2011;Bühler et al, 2013Bühler et al, , 2018.…”