Articles | Volume 15, issue 9
https://doi.org/10.5194/tc-15-4557-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-15-4557-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Surface composition of debris-covered glaciers across the Himalaya using linear spectral unmixing of Landsat 8 OLI imagery
Adina E. Racoviteanu
CORRESPONDING AUTHOR
Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth,
UK
Lindsey Nicholson
Department of Atmospheric and Cryospheric Sciences, University
of Innsbruck, Innsbruck, Austria
Neil F. Glasser
Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth,
UK
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Cited
15 citations as recorded by crossref.
- Controls on Ice Cliff Distribution and Characteristics on Debris‐Covered Glaciers M. Kneib et al. 10.1029/2022GL102444
- Seasonal to decadal dynamics of supraglacial lakes on debris-covered glaciers in the Khumbu region, Nepal L. Zeller et al. 10.5194/tc-18-525-2024
- Debris-covered glacier systems and associated glacial lake outburst flood hazards: challenges and prospects A. Racoviteanu et al. 10.1144/jgs2021-084
- Spatio-Temporal Evolution of Glacial Lakes in the Tibetan Plateau over the Past 30 Years X. Dou et al. 10.3390/rs15020416
- An integrated deep learning and object-based image analysis approach for mapping debris-covered glaciers D. Thomas et al. 10.3389/frsen.2023.1161530
- Glacier and Snow Cover Dynamics and Their Affecting Factors on the Pamir Plateau Section of the China–Pakistan Economic Corridor Y. Han et al. 10.3390/land14040880
- Current and Near-Term Earth-Observing Environmental Satellites, Their Missions, Characteristics, Instruments, and Applications S. Ustin & E. Middleton 10.3390/s24113488
- Evolution of Supraglacial Lakes from 1990 to 2020 in the Himalaya–Karakoram Region Using Cloud-Based Google Earth Engine Platform R. Sahu et al. 10.1007/s12524-023-01773-2
- Multispectral Characteristics of Glacier Surface Facies (Chandra-Bhaga Basin, Himalaya, and Ny-Ålesund, Svalbard) through Investigations of Pixel and Object-Based Mapping Using Variable Processing Routines S. Jawak et al. 10.3390/rs14246311
- Non-linear spectral unmixing for monitoring rapidly salinizing coastal landscapes M. Sarupria et al. 10.1016/j.rse.2025.114642
- Spatial Validation of Spectral Unmixing Results: A Systematic Review R. Cavalli 10.3390/rs15112822
- Mass Balance of Maritime Glaciers in the Southeastern Tibetan Plateau during Recent Decades X. Lyu et al. 10.3390/su16167118
- Land surface modeling informed by earth observation data: toward understanding blue–green–white water fluxes in High Mountain Asia P. Buri et al. 10.1080/10095020.2024.2330546
- Interannual spatio-temporal evolution of the supraglacial lakes on the Belvedere Glacier between 2000 and 2023 L. Brodský et al. 10.14712/23361980.2024.24
- Novel Machine Learning Method Integrating Ensemble Learning and Deep Learning for Mapping Debris-Covered Glaciers Y. Lu et al. 10.3390/rs13132595
14 citations as recorded by crossref.
- Controls on Ice Cliff Distribution and Characteristics on Debris‐Covered Glaciers M. Kneib et al. 10.1029/2022GL102444
- Seasonal to decadal dynamics of supraglacial lakes on debris-covered glaciers in the Khumbu region, Nepal L. Zeller et al. 10.5194/tc-18-525-2024
- Debris-covered glacier systems and associated glacial lake outburst flood hazards: challenges and prospects A. Racoviteanu et al. 10.1144/jgs2021-084
- Spatio-Temporal Evolution of Glacial Lakes in the Tibetan Plateau over the Past 30 Years X. Dou et al. 10.3390/rs15020416
- An integrated deep learning and object-based image analysis approach for mapping debris-covered glaciers D. Thomas et al. 10.3389/frsen.2023.1161530
- Glacier and Snow Cover Dynamics and Their Affecting Factors on the Pamir Plateau Section of the China–Pakistan Economic Corridor Y. Han et al. 10.3390/land14040880
- Current and Near-Term Earth-Observing Environmental Satellites, Their Missions, Characteristics, Instruments, and Applications S. Ustin & E. Middleton 10.3390/s24113488
- Evolution of Supraglacial Lakes from 1990 to 2020 in the Himalaya–Karakoram Region Using Cloud-Based Google Earth Engine Platform R. Sahu et al. 10.1007/s12524-023-01773-2
- Multispectral Characteristics of Glacier Surface Facies (Chandra-Bhaga Basin, Himalaya, and Ny-Ålesund, Svalbard) through Investigations of Pixel and Object-Based Mapping Using Variable Processing Routines S. Jawak et al. 10.3390/rs14246311
- Non-linear spectral unmixing for monitoring rapidly salinizing coastal landscapes M. Sarupria et al. 10.1016/j.rse.2025.114642
- Spatial Validation of Spectral Unmixing Results: A Systematic Review R. Cavalli 10.3390/rs15112822
- Mass Balance of Maritime Glaciers in the Southeastern Tibetan Plateau during Recent Decades X. Lyu et al. 10.3390/su16167118
- Land surface modeling informed by earth observation data: toward understanding blue–green–white water fluxes in High Mountain Asia P. Buri et al. 10.1080/10095020.2024.2330546
- Interannual spatio-temporal evolution of the supraglacial lakes on the Belvedere Glacier between 2000 and 2023 L. Brodský et al. 10.14712/23361980.2024.24
1 citations as recorded by crossref.
Latest update: 23 Apr 2025
Short summary
Supraglacial debris cover comprises ponds, exposed ice cliffs, debris material and vegetation. Understanding these features is important for glacier hydrology and related hazards. We use linear spectral unmixing of satellite data to assess the composition of map supraglacial debris across the Himalaya range in 2015. One of the highlights of this study is the automated mapping of supraglacial ponds, which complements and expands the existing supraglacial debris and lake databases.
Supraglacial debris cover comprises ponds, exposed ice cliffs, debris material and vegetation....