Mapping extreme avalanche cycles in Greenland using radar remote sensing data
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Insinööritieteiden korkeakoulu |
Master's thesis
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en
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60+9
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Abstract
This study addresses the knowledge gap in comprehensive avalanche statistics for Greenland, highlighting the need for research in this area due to the potential risks avalanches pose to both humans and infrastructure. Utilizing Sentinel-1 Synthetic Aperture Radar (SAR) images images, this research demonstrates a reliable method for identifying avalanches under any weather conditions, offering a solution when local observations are unfeasible. A detailed analysis of an extreme avalanche cycle in May 2023 is conducted, incorporating field observations, Sentinel-1 SAR data, weather records, reanalysis, and optical satellite imagery from Sentinel-2. By combining spaceborne observations with meteorological data, we show the feasibility of systematically detecting and describe avalanche events in inaccessible regions. The study compares manual and automated detection methods, discussing their limitations and suggesting directions for future improvements. The integration of weather data enables the identification of the meteorological events triggering avalanches, a factor of increasing importance as climate change is expected to intensify such extreme weather phenomena in the future.Description
Supervisor
Praks, JaanThesis advisor
Sandberg Sørensen, LouiseMarcer, Marco