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publications

Remote Sensing of Antarctic Glacier and Ice-Shelf Front Dynamics - A Review

Published in Remote Sensing, 2018

Recommended citation: Baumhoer, C. und Dietz, A. und Dech, S. und Kuenzer, C. (2018): Remote Sensing of Antarctic Glacier and Ice-Shelf Front Dynamics - A Review. Remote Sensing, 10 (9), 1445. https://doi.org/10.3390/rs10091445.
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Automated Extraction of Antarctic Glacier and Ice Shelf Fronts from Sentinel-1 Imagery Using Deep Learning

Published in Remote Sensing, 2019

Recommended citation: Baumhoer, C. und Dietz, A. und Kneisel, C. und Kuenzer, C. (2019): Automated Extraction of Antarctic Glacier and Ice Shelf Fronts from Sentinel-1 Imagery Using Deep Learning. Remote Sensing, 11 (21), 2529. https://doi.org/10.3390/rs11212529.
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HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline.

Published in IEEE Transactions on Geoscience and Remote Sensing, 2021

Recommended citation: Heidler, K., Mou, L., Baumhoer, C., Dietz, A., Zhu, X. (2021): HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/TGRS.2021.3064606.
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Remote Sensing of the Mountain Cryosphere: Current Capabilities, and Future Opportunities for Research.

Published in Progress in Physical Geography, 2021

Recommended citation: Taylor, L., Quincey, D., Smith, M., Baumhoer, C., McMillan, M., Mansell, D. (2021): Remote Sensing of the Mountain Cryosphere: Current Capabilities, and Future Opportunities for Research. Progress in Physical Geography. https://doi.org/10.1177/03091333211023690.
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Environmental Drivers of Circum-Antarctic Glacier and Ice Shelf Front Retreat over the Last Two Decades.

Published in The Cryosphere, 2021

Recommended citation: Baumhoer, C., A. J. Dietz, C. Kneisel, H. Paeth, und C. Kuenzer (2021): Environmental Drivers of Circum-Antarctic Glacier and Ice Shelf Front Retreat over the Last Two Decades. The Cryosphere. https://doi.org/10.5194/tc-2020-224.
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Drought in Northern Italy: Long Earth Observation Time Series Reveal Snow Line Elevation to Be Several Hundred Meters Above Long-Term Average in 2022

Published in Remote Sensing, 2022

Recommended citation: Koehler, J., Dietz, A. J., Zellner, P., Baumhoer, C. A., Dirscherl, M., Cattani, L., Vlahović, Ž., Alasawedah, M. H., Mayer, K., Haslinger, K., Bertoldi, G., Jacob, A., and Kuenzer, C.(2022): Drought in Northern Italy: Long Earth Observation Time Series Reveal Snow Line Elevation to Be Several Hundred Meters Above Long-Term Average in 2022, Remote Sensing, 14, https://doi.org/10.3390/rs14236091.
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IceLines – A new data set of Antarctic ice shelf front positions

Published in Nature Scientific Data, 2023

Recommended citation: Baumhoer, C. A., Dietz, A. J., Heidler, K., and Kuenzer, C. (2023): IceLines – A new data set of Antarctic ice shelf front positions, Sci Data, 10, 138, https://doi.org/10.1038/s41597-023-02045-x.
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Multi-Sensor Glacier Surface Classification Using Confidence-Aware Explainable Inverse-Mapping Neural Network

Published in Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024

Recommended citation: G. Joshi, C. Baumhoer, A. Dietz, R. Natusaki, A. Hirose (2024): Multi-Sensor Glacier Surface Classification Using Confidence-Aware Explainable Inverse-Mapping Neural Network, Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
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Vegetation Changes in the Arctic: A Review of Earth Observation Applications

Published in Remote Sensing, 2024

Recommended citation: Wenzl, M., Baumhoer, C.A., Dietz, A.J., Kuenzer, C., (2024): Vegetation Changes in the Arctic: A Review of Earth Observation Applications. Remote Sensing 16, 4509. https://doi.org/10.3390/rs16234509
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Calving front positions for 42 key glaciers of the Antarctic Peninsula Ice Sheet: a sub-seasonal record from 2013 to 2023 based on a deep learning application to Landsat multispectral imagery

Published in Earth System Science Data, 2025

Recommended citation: Loebel, E., Baumhoer, C.A., Dietz, A., Scheinert, M., Horwath, M., 2025. Calving front positions for 42 key glaciers of the Antarctic Peninsula Ice Sheet: a sub-seasonal record from 2013 to 2023 based on deep-learning application to Landsat multi-spectral imagery. Earth System Science Data 17, 65–78. https://doi.org/10.5194/essd-17-65-2025 .
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Automated crevasse mapping for Alpine glaciers: A multitask deep neural network approach

Published in International Journal of Applied Earth Observation and Geoinformation, 2025

Recommended citation: C. A. Baumhoer, S. Leibrock, C. Zapf, W. Beer, und C. Kuenzer (2025): „Automated crevasse mapping for Alpine glaciers: A multitask deep neural network approach“, International Journal of Applied Earth Observation and Geoinformation, Bd. 139, S. 104495, doi: https://doi.org/10.1016/j.jag.2025.104495.
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Snow Cover Trends in the Chilean Andes Derived from 39 Years of Landsat Data and a Projection for the Year 2050

Published in Remote Sensing, 2025

Recommended citation: Dietz, A.J., Köhler, J., Obrecht, L., Rößler, S., Baumhoer, C.A., Cereceda-Balic, F., Saavedra, F. (2025): Snow Cover Trends in the Chilean Andes Derived from 39 Years of Landsat Data and a Projection for the Year 2050. Remote Sensing 17, 1651. https://doi.org/10.3390/rs17091651
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Advancing Supraglacial Lake Mapping in Antarctica: A Deep Learning Approach Using Sentinel-2 Imagery

Published in Earth System Data Science, 2025

Recommended citation: Koehler, J., Baumhoer, C., Wouters, B., Lhermitte, S., and Dietz, A.: Advancing Supraglacial Lake Mapping in Antarctica: A Deep Learning Approach Using Sentinel-2 Imagery, Environmental Data Science, https://doi.org/10.33774/coe-2025-6svt4, accepted.
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Sub-seasonal variability and multi-year trends in glacier area change and ice speed on the Antarctic Peninsula

Published in The Cryosphere Discussions, 2025

Recommended citation: Leibrock, S., Slater, R. A. W., Hogg, A. E., and Baumhoer, C. A.: Sub-seasonal variability and multi-year trends in glacier area change and ice speed on the Antarctic Peninsula, https://doi.org/10.5194/egusphere-2025-5492, 15 December 2025.
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Ski Areas and Snow Reliability Decline in the European Alps Under Increasing Global Warming—A Remote Sensing Perspective

Published in Remote Sensing, 2026

Recommended citation: Schilling, S.; Koehler, J.; Baumhoer, C.; Krause, C.; Aigner, G.; Vydra, C.; Kuenzer, C.; Dietz, A. Ski Areas and Snow Reliability Decline in the European Alps Under Increasing Global Warming—A Remote Sensing Perspective. Remote Sens. 2026, 18, 491. https://doi.org/10.3390/rs18030491
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Shelf-Bench: A benchmark dataset for Antarctic ice shelf front and coastline delineation from multi-sensor radar satellite data

Published in Earth System Science Data Discussions, 2026

Recommended citation: Baumhoer, C. A., Morgan, A. B., Hou, X., Fromentin, J. L., Hoeser, T., Dietz, A. J., Markham, A., Stevens, L. A., and Kuenzer, C.: Shelf-Bench: A benchmark dataset for Antarctic ice shelf front and coastline delineation from multi-sensor radar satellite data, Earth System Science Data Discussions, 1–33, https://doi.org/10.5194/essd-2025-758 , 2026.
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PolarLakes: A Bi-Weekly Dataset of Supraglacial Lakes on Antarctic Ice Shelves from Multi-Sensor Satellite Observations (2015-2024)

Published in Earth System Science Discussions, 2026

Recommended citation: Baumhoer, C. A., Koehler, J., Wouters, B., Lhermitte, S., Dietz, A. J., and Kuenzer, C.: PolarLakes: A Bi-Weekly Dataset of Supraglacial Lakes on Antarctic Ice Shelves from Multi-Sensor Satellite Observations (2015-2024), Earth System Science Data Discussions, 1–24, https://doi.org/10.5194/essd-2025-569 , in review.
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Remote Sensing Foundation Models for real-world Earth Observation Applications - A Review

Published in Preprint, 2026

Recommended citation: Leibrock, S., Baumhoer, C., Hoeser, T., Dietz, A., and Kuenzer, C.: Remote Sensing Foundation Models for real-world Earth Observation Applications - A Review, https://doi.org/10.2139/ssrn.7298758, 9 August 2026., 2026.
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talks

Automatic mapping of Antarctic glacier and ice shelf fronts from Sentinel-1 imagery – A deep learning approach

Published: December 01, 2019

The AI-CORE Project - Artificial Intelligence for Cold Regions

Published: September 05, 2022

Keeping track of change – Monitoring Antarctic calving front dynamics with earth observation and deep learning

Published: June 14, 2023

USA meets the Alps: Alpine Innovation

Published: September 19, 2023

The future of Arctic research

Published: October 10, 2023

The potential of earth observation for cold and polar regions

Published: October 17, 2023

How Passion Thrives Science – Observing the Earth as a Scientist and Mountaineer

Published: June 26, 2024

Seasonal evolution of Antarctic supraglacial lakes in the Sentinel satellite era

Published: June 25, 2025

Safer Route Planning on Alpine Glaciers: A New Crevasse Dataset

Published: September 14, 2025

Trails from Above: The potential of Earth Observation and AI for route planning and trail management. Artificial Intelligence – Opportunities and threats for trails and path management

Published: October 11, 2025

04/2026 Data-Driven Benchmarking of Deep Learning Models for Antarctic Coastline Segmentation Using Earth Observation Imagery, Univeristät Bonn.
02/2026 Current Status, Trends, and Future Challenges of the Alpine Cryosphere, Illustrated by an Example from the Hohe Tauern National Park, JMU Würzburg.
02/2026 Analyse und Detektion von Gletscherspalten in den österreichischen Alpen: Eine raumbezogene Analyse auf Basis von Fernerkundungsdaten, Haupt Universität Wien
02/2025 High Performance Computing for Earth Observation Time Series Analysis: A Case Study on Glacier Dynamics on the Antarctic Peninsula, JMU
05/2024 Mapping Alpine glacier crevasses from aerial remote sensing data with a multitask deep neural network, in collaboration with the German Alpine Club (DAV) (3-month innovation lab)
08/2023 Extracting historic Antarctic ice shelf fronts with SAR imagery and deep learning, University Utrecht, 3-month internship
02/2023 Analysis of ice shelf front dynamics in Pine Island Bay (Antarctica) based on long-term SAR time series and deep learning, University of Würzburg
since 2019 Supervision of over 16 8-week internships from various national and international universities

Celia A. Baumhoer

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