Glacier Snowline Determination from Terrestrial Laser Scanning Intensity Data

Prantl, Hannah; Nicholson, Lindsey; Sailer, Rudolf; Hanzer, Florian; Juen, Irmgard F.; Rastner, Philipp

doi:10.3390/geosciences7030060

Open AccessArticle

Glacier Snowline Determination from Terrestrial Laser Scanning Intensity Data

by

Hannah Prantl

^1,*,

Lindsey Nicholson

²,

Rudolf Sailer

¹

,

Florian Hanzer

¹,

Irmgard F. Juen

² and

Philipp Rastner

³

¹

Institute of Geography, University of Innsbruck, 6020 Innsbruck, Austria

²

Institute of Atmospheric and Cryospheric Sciences, University of Innsbruck, 6020 Innsbruck, Austria

³

Department of Geography, University of Zurich, 8006 Zurich, Switzerland

^*

Author to whom correspondence should be addressed.

Geosciences 2017, 7(3), 60; https://doi.org/10.3390/geosciences7030060

Submission received: 29 April 2017 / Revised: 28 June 2017 / Accepted: 10 July 2017 / Published: 17 July 2017

(This article belongs to the Special Issue Cryosphere)

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Abstract

Accurately identifying the extent of surface snow cover on glaciers is important for extrapolating end of year mass balance measurements, constraining the glacier surface radiative energy balance and evaluating model simulations of snow cover. Here, we use auxiliary information from Riegl VZ-6000 Terrestrial Laser Scanner (TLS) return signals to accurately map the snow cover over a glacier throughout an ablation season. Three classification systems were compared, and we find that supervised classification based on TLS signal intensity alone is outperformed by a rule-based classification employing intensity, surface roughness and an associated optical image, which achieves classification accuracy of 68–100%. The TLS intensity signal shows no meaningful relationship with surface or bulk snow density. Finally, we have also compared our Snow Line Altitude (SLA) derived from TLS with SLA derived from the model output, as well as one Landsat image. The results of the model output track the SLA from TLS well, however with a positive bias. In contrast, automatic Landsat-derived SLA slightly underestimates the SLA from TLS. To conclude, we demonstrate that the snow cover extent can be mapped successfully using TLS, although the snow mass remains elusive.

Keywords: terrestrial laser scanning; surface classification; snow line altitudes

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MDPI and ACS Style

Prantl, H.; Nicholson, L.; Sailer, R.; Hanzer, F.; Juen, I.F.; Rastner, P. Glacier Snowline Determination from Terrestrial Laser Scanning Intensity Data. Geosciences 2017, 7, 60. https://doi.org/10.3390/geosciences7030060

AMA Style

Prantl H, Nicholson L, Sailer R, Hanzer F, Juen IF, Rastner P. Glacier Snowline Determination from Terrestrial Laser Scanning Intensity Data. Geosciences. 2017; 7(3):60. https://doi.org/10.3390/geosciences7030060

Chicago/Turabian Style

Prantl, Hannah, Lindsey Nicholson, Rudolf Sailer, Florian Hanzer, Irmgard F. Juen, and Philipp Rastner. 2017. "Glacier Snowline Determination from Terrestrial Laser Scanning Intensity Data" Geosciences 7, no. 3: 60. https://doi.org/10.3390/geosciences7030060

APA Style

Prantl, H., Nicholson, L., Sailer, R., Hanzer, F., Juen, I. F., & Rastner, P. (2017). Glacier Snowline Determination from Terrestrial Laser Scanning Intensity Data. Geosciences, 7(3), 60. https://doi.org/10.3390/geosciences7030060

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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Glacier Snowline Determination from Terrestrial Laser Scanning Intensity Data

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