Preprints
https://doi.org/10.5194/tc-2022-164
https://doi.org/10.5194/tc-2022-164
 
18 Aug 2022
18 Aug 2022
Status: this preprint is currently under review for the journal TC.

Automated ArcticDEM iceberg detection tool: insights into area and volume distributions, and their potential application to satellite imagery and modelling of glacier-iceberg-ocean systems

Connor Shiggins, James Lea, and Stephen Brough Connor Shiggins et al.
  • Department of Geography and Planning, School of Environmental Sciences, University of Liverpool, Liverpool, L69 7ZT, United Kingdom

Abstract. Iceberg calving accounts for up to half of mass loss from the Greenland Ice Sheet (GrIS), with their size distributions providing insights into glacier calving dynamics, and impacting fjord environments through their melting and subsequent freshwater release. Iceberg area and volume data for the GrIS are currently limited to a handful of fjord locations, while existing approaches to iceberg detection are often time consuming and are not always suited for long time series analysis over large spatial scales. This study presents a fully automated workflow for the detection of icebergs within Google Earth Engine using high spatial resolution timestamped ArcticDEM (Arctic Digital Elevation Model) strip data. This is applied to three glaciers that exhibit a range of different iceberg densities and size distributions: Sermeq Kujalleq (Jakobshavn Isbræ), Umiammakku Isbræ and Kangiata Nunaata Sermia. A total of 39 ArcticDEM scenes are analysed, detecting a total of 163,738 icebergs in 6 minutes to 2 hours for each glacier depending on the number of DEMs available and total area analysed, comparing well with manually digitised outlines. Results reveal two distinct iceberg distributions at Sermeq Kujalleq and Kangiata Nunaata Sermia where iceberg density is high, and one distribution at Umiammakku Isbræ where iceberg density is low. Small icebergs are found to account for over 80 % of each glacier’s icebergs however, they only contribute to 10–37 % of total iceberg volume suggesting that large icebergs are proportionally more important for glacier mass loss and as fjord freshwater reservoirs. The overall dataset is used to construct new area to volume conversions (with associated uncertainties) that can be applied to two-dimensional iceberg outlines derived from optical or synthetic aperture radar imagery. When data are expressed in terms of total iceberg count and volume, insight is provided into iceberg distributions that have potential applicability to observations and modelling of iceberg calving behaviour and fjord freshwater fluxes. Due to the speed and automated nature of our approach, this workflow offers the potential to interrogate iceberg data on a pan-Arctic scale where there is sufficient ArcticDEM coverage.

Connor Shiggins et al.

Status: open (until 13 Oct 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Connor Shiggins et al.

Connor Shiggins et al.

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Short summary
Iceberg detection is spatially and temporally limited around the Greenland Ice Sheet. This study presents a new, accessible workflow to automatically detect icebergs from timestamped ArcticDEM strip data. The workflow successfully produces comparable output to manual digitisation, with results revealing new iceberg area-to-volume conversion equations that can be widely applied to datasets where only iceberg outlines can be extracted (e.g. optical and SAR imagery).