SOURCE-LINKED INTELLIGENCE

Ice Shelf Damage Characterization and Monitoring around Antarctica

CORDIS · observation · Publication date unknown

rvation to constrain them. The aim of the IceDaM project is to quantify and understand the evolution of damage on ice shelves around Antarctica. My team and I will first use a novel approach based on deep learning to automatically identify the evolution of fractures and their characteristics on satellite imagery. By combining this record with inversions from a high-order ice flow model, we will quantify the links between fractures and changes in ice rigidity, which controls the strength of ice shelves. To better understand the damage variability, we will measure the evolution of key variables that positively impact the rheological weakening of ice shelves. These time series will be analyzed in a unique fashion, to determine the major processes that led to the evolution of damage in the satellite observation era. Based on these results, we will set up the first sentinel of ice shelves by systematically mapping the evolution of fractures in near real time. This will be used to establish new vulnerability indices, based on changes in ice rigidity and their impact on glacier mass balance

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recordType

award

status

SIGNED

region

EU

value

1478971

unit

EUR