Comparison of data-driven models for avalanche susceptibility assessment in Andorra
Cita com:
hdl:2117/399079
Document typeMaster thesis
Date2023-09
Rights accessOpen Access
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Abstract
Snow avalanches are defined as a mass of snow that rapidly flows down a sloping surface, such as a hill or a mountain. Depending on their velocity and volume they can have highly destructive force and pose major threat to people, property, infrastructure, and ecosystems. Andorra is a small, mountainous country located in the Axial Zone of the central Pyrenees mountain range in southwestern Europe, enclosed by France and Spain. It is exposed to several natural hazards including snow avalanches. The latter occur in the country several times per year and the popularity of winter tourism in the area results in high risk levels. Due to the frequency of the events, Andorra maintains a long avalanche inventory since the 1980’s. Although the authorities have developed advanced regulations in terms of managing risk, have put in place a series of monitoring systems, as well as protection measures for avalanches, currently, there is not a forecasting tool available, and the issued warnings are based on weather observations and experience.
The aim of this master thesis has been to evaluate the suitability of data-driven models to assess susceptibility and map initiation areas of snow avalanches in Andorra. This aim was formulated as a classification task and the machine learning algorithms that were brought to the test included the Decision Tree, Random Forest, Adaptive Boosting, Gradient Boosting, Extreme Gradient Boosting, Logistic Regression, Support Vector Classifier, and Neural Network. The models received as input topographical information of the study area, derived by GIS analysis of a 5x5 m DEM and a land cover map, interpolated weather station data, snow cover information from Landsat 8 and the susceptibility to shallow landslides acquired by Shalstab. The obtained results were satisfactory, with achieved accuracies of 80% or higher for all the models.
DegreeMÀSTER UNIVERSITARI ERASMUS MUNDUS EN GESTIÓ DEL RISC PER INUNDACIÓ (Pla 2019)
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Georgia Manou - final thesis.pdf | 6,122Mb | View/Open |