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The Cryosphere An interactive open-access journal of the European Geosciences Union
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Short summary
High mountain glaciers are often characterized by supraglacial debris comprising ponds, exposed ice cliffs and dry vegetation. Quantifying the composition of these surfaces is essential to understand glacier hydrology and related hazards. We used linear spectral unmixing of satellite data to map supraglacial features across the Himalaya. One of the highlights of this study is the automated mapping of supraglacial ponds, which complements and expands the existing lake databases for the year 2015.
Preprints
https://doi.org/10.5194/tc-2020-372
https://doi.org/10.5194/tc-2020-372

  08 Jan 2021

08 Jan 2021

Review status: this preprint is currently under review for the journal TC.

Surface composition of debris-covered glaciers across the Himalaya using spectral unmixing and multi-sensor imagery

Adina E. Racoviteanu1, Lindsey Nicholson2, and Neil F. Glasser1 Adina E. Racoviteanu et al.
  • 1Department of Geography and Earth Sciences, Aberystwyth University, UK
  • 2Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Austria

Abstract. The Hindu-Kush Himalaya mountain range is characterized by highly glacierized, complex, dynamic topography. The ablation area of these glaciers is often covered a highly heterogeneous debris cover mantle comprising ponds, steep and shallow slopes of various aspects, variable debris thickness and exposed ice cliffs. These surface elements are associated with differing ice ablation rates, and understanding the composition of the glacier surface is essential for a proper understanding of glacier hydrology and glacier-related hazards. Here we use high-resolution Pleiades (2 m) and RapidEye imagery (5 m) combined with Landsat Operational Land Imager (OLI) imagery (30 m) to estimate the composition of debris-covered glacier tongues across the Himalaya around the year 2015. We use linear spectral unmixing to map various types of debris, clean ice, supraglacial ponds and vegetation on debris-covered glaciers across the mountain range. We develop the spectral unmixing methods in the Khumbu region of eastern Nepal, and then apply them over the entire Himalaya (a glacier area of 2,254 km2). This allowed us to convert 30 m fractional maps into finer classification maps and to estimate the composition of debris-covered glaciers at various spatial scales. Debris-covered glaciers across the mountain range comprised 2.1 % supraglacial ponds, 12.8 % dark debris, 60.9 % light debris and 4.5 % supra glacial vegetation, with negligible amounts of clean ice and clouds and unclassified areas. Supraglacial ponds were more prevalent in the monsoon-influenced central-eastern Himalaya (up to 4 % of the debris cover area) compared to the monsoon-dry transition zone (only 0.3 %). The automated fractional supraglacial pond maps developed here serve to complement and improve the accuracy of existing regional lake datasets. They also provide a basis for exploring the turbidity of lakes and ponds as indicators of glacier change processes, and to monitor the evolution of ponds in the context of glacial hazards.

Adina E. Racoviteanu et al.

Status: open (until 05 Mar 2021)

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Adina E. Racoviteanu et al.

Data sets

Supraglacial features of debris covered glaciers in the Himalaya from Landsat spectral umixing and Pleiades Racoviteanu, A. E. https://doi.org/10.5281/zenodo.4421857

Adina E. Racoviteanu et al.

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Short summary
High mountain glaciers are often characterized by supraglacial debris comprising ponds, exposed ice cliffs and dry vegetation. Quantifying the composition of these surfaces is essential to understand glacier hydrology and related hazards. We used linear spectral unmixing of satellite data to map supraglacial features across the Himalaya. One of the highlights of this study is the automated mapping of supraglacial ponds, which complements and expands the existing lake databases for the year 2015.
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