Damage detection on antarctic ice shelves using the normalised radon transform

Izeboud, Maaike; Lhermitte, Stef

doi:10.1016/j.rse.2022.113359

Cited by 13 publications

(14 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The ability to observe crevasses in 3-D provides a major advance over two-dimensional mapping from imagery alone 27,28 . We have observed significant increases in crevasse volume in pre-existing crevasse fields at low elevations (marine-terminating outlets).…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, improved observations are required to develop and validate models of fracture formation and propagation 25 and parameterise their behaviour in models of ice sheet dynamics and hydrology 6,26 . Optical satellite observation methods have progressed from manual delineation 4 to computer vision 27,28 and machine learning 29,30 approaches. However, these are limited to assessing crevasse presence without critical information about crevasse depth, and attempts to map geometry have thus far been limited to profiles 21 .…”

mentioning

confidence: 99%

See 1 more Smart Citation

Increased crevassing across accelerating Greenland Ice Sheet margins

Chudley,

Howat,

King

et al. 2024

Preprint

View full text Add to dashboard Cite

The extent of surface crevassing on the Greenland Ice Sheet is a large source of uncertainty in processes controlling mass loss, including iceberg calving, ice rheology, and water routing. However, no work to date has comprehensively mapped the location of surface crevasses or examined their evolution through time. Here, we use high-resolution digital elevation models to infer the 3-dimensional evolution of crevasse fields across the Greenland Ice Sheet between 2016 and 2021. Whilst the change in the total volume of crevasses was within error (+4.3 ± 5.9%), large and significant increases occurred at accelerating marine-terminating sectors of the ice sheet (up to +25.3 ± 10.1%). These increases were offset only by a reduction in crevasse volume in the central west sector (-14.2 ± 3.2%), particularly at Sermeq Kujalleq (Jakobshavn Isbræ), which underwent a temporary slowdown over the study period. Changes in crevasse volume correlate strongly with antecedent discharge changes, indicating that Greenland’s acceleration is affecting significant increases in crevassing on a timescale of less than five years. This rapid response provides a mechanism for mass-loss-promoting feedbacks on sub-decadal timescales, including increased calving, faster flow, and accelerated water transfer to the bed.

show abstract

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Increased crevassing across accelerating Greenland Ice Sheet margins

Chudley,

Howat,

King

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…However, manual or semi-automated crevasse identification is both subjective and time-consuming, preventing multi-temporal mapping of crevasses over large spatial areas. Therefore, a range of fully automated crevasse mapping techniques have also been developed: Bhardwaj and others (2016) used a simple Landsat band ratio technique to map small crevasses on Shaune Garang glacier (Himalaya), Gong and others (2018) used the Radon transform to evaluate linear features on a surging outlet of Austfonna (Svalbard), Chudley and others (2021) compared a Random Forest classification to crevasse maps from high-resolution elevation data in Greenland, Christmann and others (2021) compared DEM-derived and manually mapped crevasse fields over Greenland to stress change maps, Lai and others (2020) used a neural network to identify Antarctica-wide rifts using MODIS Mosaic of Antarctica imagery, Zhao and others (2022) applied deep learning to Sentinel-1 radar imagery to map fractures in Antarctic ice shelves, and Izeboud and Lhermitte (2023) develop a method for automated crevasse detection using a normalized radon transform. Despite the recent advances in automated crevasse mapping, most existing techniques either require an extensive training dataset (e.g.…”

Section: Introductionmentioning

confidence: 99%

Crevasse density, orientation and temporal variability at Narsap Sermia, Greenland

Vries

Lea²,

Ashmore³

2023

J. Glaciol.

View full text Add to dashboard Cite

Mass loss from iceberg calving at marine-terminating glaciers is one of the largest and most poorly constrained contributors to sea-level rise. However, our understanding of the processes controlling ice fracturing and crevasse evolution is incomplete. Here, we use Gabor filter banks to automatically map crevasse density and orientation through time on a ~150 km2 terminus region of Narsap Sermia, an outlet glacier of the southwest Greenland ice sheet. We find that Narsap Sermia is dominated by transverse (flow-perpendicular) crevasses near the ice front and longitudinal (flow-aligned) crevasses across its central region. Measured crevasse orientation varies on sub-annual timescales by more than 45 $^\circ$ in response to seasonal velocity changes, and also on multi-annual timescales in response to broader dynamic changes and glacier retreat. Our results show a gradual up-glacier propagation of the zone of flow-transverse crevassing coincident with frontal retreat and acceleration occurring in 2020/21, in addition to sub-annual crevasse changes primarily in transition zones between longitudinal to transverse crevasse orientation. This provides new insight into the dynamics of crevassing at large marine-terminating glaciers and a potential approach for the rapid identification of glacier dynamic change from a single pair of satellite images.

show abstract

“…Work by Lai et al (2020) included the continent-wide extraction of ice-shelf crevasse locations from optical satellite data with the application of a convolutional neural network. More recently, Izeboud and Lhermitte (2023) showed the efficacy of a method of ice shelf fracture and orientation detection based on the application of radon-transforms to satellite images. Finally, previous work by Surawy-Stepney et al (2023) presented quantitative analysis of the structural properties of the Thwaites Glacier Ice Tongue using crevasse timeseries generated from Sentinel-1 SAR data using a neural network.…”

Section: Introductionmentioning

confidence: 99%

Mapping Antarctic Crevasses and their Evolution with Deep Learning Applied to Satellite Radar Imagery

Surawy-Stepney

Hogg

Cornford

et al. 2023

Preprint

View full text Add to dashboard Cite

Abstract. The fracturing of glaciers and ice shelves in Antarctica influences their dynamics, and may introduce as-yet poorly understood feedbacks and hysteresis into the ice sheet system. Therefore, data on the evolving distribution of crevasses is required to better understand the evolution of the ice sheet, though such data has traditionally been difficult and time consuming to generate. Here, we present an automated method of mapping crevasses on grounded and floating ice with the application of convolutional neural networks to Sentinel-1 synthetic aperture radar backscatter images acquired between 2015 and 2022. We apply this method across Antarctica to produce a 7-and-a-half year record of composite fracture maps at monthly intervals and 50 m spatial resolution, showing the distribution of crevasses around the majority of the ice sheet margin. We develop a method of quantifying changes to the density of ice shelf fractures using the timeseries of crevasse maps, and show increases in crevassing on the Thwaites and Pine Island ice shelves over the observational period, with observed changes elsewhere in the Amundsen Sea dominated by the advection of existing crevasses. Using stress fields computed using the BISICLES ice sheet model, we show that much of this structural change has occurred in strongly buttressing regions of these ice shelves, indicating a recent and ongoing link between fracturing and the developing dynamics of the Amundsen Sea Sector.

show abstract

Damage detection on antarctic ice shelves using the normalised radon transform

Cited by 13 publications

References 47 publications

Increased crevassing across accelerating Greenland Ice Sheet margins

Increased crevassing across accelerating Greenland Ice Sheet margins

Crevasse density, orientation and temporal variability at Narsap Sermia, Greenland

Mapping Antarctic Crevasses and their Evolution with Deep Learning Applied to Satellite Radar Imagery

Contact Info

Product

Resources

About