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Earth Surface Dynamics An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/esurf-2020-40
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-2020-40
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  17 Jun 2020

17 Jun 2020

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This preprint is currently under review for the journal ESurf.

GERALDINE (Google earth Engine supRaglAciaL Debris INput dEtector) – A new Tool for Identifying and Monitoring Supraglacial Landslide Inputs

William D. Smith1, Stuart A. Dunning1, Stephen Brough1,2, Neil Ross1, and Jon Telling3 William D. Smith et al.
  • 1School of Geography, Politics and Sociology, Newcastle University, Newcastle upon Tyne, UK
  • 2Department of Geography and Planning, School of Environmental Sciences, University of Liverpool, UK
  • 3School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, UK

Abstract. Rock avalanches, a high-magnitude, long runout form of bedrock landslide, are thought to increase in frequency as a paraglacial response to ice-retreat/thinning, and arguably, due to warming temperatures/degrading permafrost above current glaciers. However, our ability to test these assumptions by quantifying the temporal sequencing of debris inputs over large spatial and temporal extents is limited in areas with glacier ice. Discrete landslide debris inputs, particularly in accumulation areas are rapidly ‘lost’, being reworked by motion and icefalls, and/or covered by snowfall. Although large landslides can be detected and located using their seismic signature, small to medium-sized landslides, particularly supraglacially deposited landslides which feature a quiet runout over snow, frequently go undetected because their seismic signature is less than the noise floor. Here, we present GERALDINE (Google earth Engine supRaglAciaL Debris INput dEtector): a new open-source tool leveraging Landsat 4–8 satellite imagery and Google Earth Engine. GERALDINE outputs maps of new supraglacial debris additions within user-defined areas and time ranges, providing a user with a reference map, from which large debris inputs such as supraglacial rock avalanches can be rapidly identified. We validate the effectiveness of GERALDINE outputs using published rock-avalanche inventories, then demonstrate its potential by identifying two previously unknown, large (> 2 km2) supraglacial debris inputs onto glaciers in the Hayes Range, Alaska, one of which was not detected seismically. GERALDINE is a first step towards a revised global magnitude-frequency of rock avalanche inputs onto glaciers over the 37 years of Landsat Thematic Mapper imagery.

William D. Smith et al.

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Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

William D. Smith et al.

Data sets

Validation dataset W. D. Smith, S. A. Dunning, S. Brough, N. Ross, and J. Telling https://doi.org/10.5281/zenodo.3524414

Model code and software

GERALDINE code W. D. Smith, S. A. Dunning, S. Brough, N. Ross, and J. Telling https://doi.org/10.5281/zenodo.3524414

William D. Smith et al.

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Short summary
Glacial landslides are difficult to detect and likely underestimated due to rapid covering or dispersal. Without improved detection rates we cannot constrain their impact on glacial dynamics, or, their potential climatically driven increases in occurrence. Here we present a new open-access tool (GERALDINE) that helps a user detect 92 % of these events over the past 37 years on a global scale. We demonstrate its ability by identifying two new, large, glacial landslides in the Hayes Range, Alaska.
Glacial landslides are difficult to detect and likely underestimated due to rapid covering or...
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