Analysis of ice shelf front dynamics in Pine Island Bay (Antarctica) based on long-term SAR time series and deep learning

Ice shelves, the floating extensions of glaciers and ice sheets, create a safety band around Antarctica. They control the flow of ice that drains into the ocean by buttressing the upstream grounded ice. Loss of ice shelf stability and integrity results in reduced buttressing and leads to increased d...

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Bibliographic Details
Main Author: Wagner, Luisa
Format: Thesis
Language:unknown
Published: 2023
Subjects:
Online Access:https://elib.dlr.de/190399/
id ftdlr:oai:elib.dlr.de:190399
record_format openpolar
spelling ftdlr:oai:elib.dlr.de:190399 2023-05-15T13:51:36+02:00 Analysis of ice shelf front dynamics in Pine Island Bay (Antarctica) based on long-term SAR time series and deep learning Wagner, Luisa 2023-01-17 https://elib.dlr.de/190399/ unknown Wagner, Luisa (2023) Analysis of ice shelf front dynamics in Pine Island Bay (Antarctica) based on long-term SAR time series and deep learning. Masterarbeit, Universität Würzburg. Dynamik der Landoberfläche Hochschulschrift NonPeerReviewed 2023 ftdlr 2023-03-06T00:16:22Z Ice shelves, the floating extensions of glaciers and ice sheets, create a safety band around Antarctica. They control the flow of ice that drains into the ocean by buttressing the upstream grounded ice. Loss of ice shelf stability and integrity results in reduced buttressing and leads to increased discharge, i.e. contribution to global sea level rise. Accurate predictions of rates of sea level rise therefore require monitoring of ice shelf dynamics. So far, the potential of SAR data for this task has hardly been exhausted. While comprehensive products exist for recent years, data of early SAR satellites has up to now only been used to a very limited extent. To fill this research gap, this thesis exploits the entire ERS and Envisat archive within West Antarctic Pine Island Bay, a region that requires particular attention due to drastic on-going changes. A deep learning based semantic segmentation approach is applied to derive a 20-year time series (1992-2011) of ice shelf front dynamics from nearly 2000 available scenes. The used HED-UNet framework proved to be transferable to this purpose. For selected test scenes, the detected ice shelf fronts deviate on average by 355 m from manual references, the segmentation accuracy is 96%. The resulting product of yearly, seasonal and monthly time series reveals individual dynamic patterns for all five investigated ice shelves. The most considerable fluctuations were found for Pine Island Ice Shelf in terms of frequency of calving events (multiple cycles of calving and re-advance) and Thwaites ice tongue in terms of size of break-up (80 km retreat in early 2002). Despite different change rates and magnitude, most ice shelves show similar signs of destabilisation. This not only manifests through retreating front positions, but also through the ice shelf geometry. Signs of weakening appear in the form of fracturing, rifting, disintegration events and the development of passive parts that no longer contribute to the buttressing effect. Thesis Antarc* Antarctic Antarctica Ice Shelf Ice Shelves Pine Island Pine Island Bay German Aerospace Center: elib - DLR electronic library Antarctic Island Bay ENVELOPE(-109.085,-109.085,59.534,59.534) Pine Island Bay ENVELOPE(-102.000,-102.000,-74.750,-74.750)
institution Open Polar
collection German Aerospace Center: elib - DLR electronic library
op_collection_id ftdlr
language unknown
topic Dynamik der Landoberfläche
spellingShingle Dynamik der Landoberfläche
Wagner, Luisa
Analysis of ice shelf front dynamics in Pine Island Bay (Antarctica) based on long-term SAR time series and deep learning
topic_facet Dynamik der Landoberfläche
description Ice shelves, the floating extensions of glaciers and ice sheets, create a safety band around Antarctica. They control the flow of ice that drains into the ocean by buttressing the upstream grounded ice. Loss of ice shelf stability and integrity results in reduced buttressing and leads to increased discharge, i.e. contribution to global sea level rise. Accurate predictions of rates of sea level rise therefore require monitoring of ice shelf dynamics. So far, the potential of SAR data for this task has hardly been exhausted. While comprehensive products exist for recent years, data of early SAR satellites has up to now only been used to a very limited extent. To fill this research gap, this thesis exploits the entire ERS and Envisat archive within West Antarctic Pine Island Bay, a region that requires particular attention due to drastic on-going changes. A deep learning based semantic segmentation approach is applied to derive a 20-year time series (1992-2011) of ice shelf front dynamics from nearly 2000 available scenes. The used HED-UNet framework proved to be transferable to this purpose. For selected test scenes, the detected ice shelf fronts deviate on average by 355 m from manual references, the segmentation accuracy is 96%. The resulting product of yearly, seasonal and monthly time series reveals individual dynamic patterns for all five investigated ice shelves. The most considerable fluctuations were found for Pine Island Ice Shelf in terms of frequency of calving events (multiple cycles of calving and re-advance) and Thwaites ice tongue in terms of size of break-up (80 km retreat in early 2002). Despite different change rates and magnitude, most ice shelves show similar signs of destabilisation. This not only manifests through retreating front positions, but also through the ice shelf geometry. Signs of weakening appear in the form of fracturing, rifting, disintegration events and the development of passive parts that no longer contribute to the buttressing effect.
format Thesis
author Wagner, Luisa
author_facet Wagner, Luisa
author_sort Wagner, Luisa
title Analysis of ice shelf front dynamics in Pine Island Bay (Antarctica) based on long-term SAR time series and deep learning
title_short Analysis of ice shelf front dynamics in Pine Island Bay (Antarctica) based on long-term SAR time series and deep learning
title_full Analysis of ice shelf front dynamics in Pine Island Bay (Antarctica) based on long-term SAR time series and deep learning
title_fullStr Analysis of ice shelf front dynamics in Pine Island Bay (Antarctica) based on long-term SAR time series and deep learning
title_full_unstemmed Analysis of ice shelf front dynamics in Pine Island Bay (Antarctica) based on long-term SAR time series and deep learning
title_sort analysis of ice shelf front dynamics in pine island bay (antarctica) based on long-term sar time series and deep learning
publishDate 2023
url https://elib.dlr.de/190399/
long_lat ENVELOPE(-109.085,-109.085,59.534,59.534)
ENVELOPE(-102.000,-102.000,-74.750,-74.750)
geographic Antarctic
Island Bay
Pine Island Bay
geographic_facet Antarctic
Island Bay
Pine Island Bay
genre Antarc*
Antarctic
Antarctica
Ice Shelf
Ice Shelves
Pine Island
Pine Island Bay
genre_facet Antarc*
Antarctic
Antarctica
Ice Shelf
Ice Shelves
Pine Island
Pine Island Bay
op_relation Wagner, Luisa (2023) Analysis of ice shelf front dynamics in Pine Island Bay (Antarctica) based on long-term SAR time series and deep learning. Masterarbeit, Universität Würzburg.
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