Articles | Volume 18, issue 1
https://doi.org/10.5194/essd-18-147-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-147-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
06 Jan 2026
Data description paper |
| 06 Jan 2026
| 06 Jan 2026
A six-year circum-Antarctic icebergs dataset (2018–2023)
Zilong Chen
School of Geospatial Engineering and Science, Sun Yat-sen University, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 51908, China
Key Laboratory of Comprehensive Observation of Polar Environment (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
Xuying Liu
Institute of Artificial Intelligence, Shaoxing University, Shaoxing 312000, China
Zhenfu Guan
School of Geospatial Engineering and Science, Sun Yat-sen University, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 51908, China
State Key Laboratory of Remote Sensing and Digital Earth, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
School of Geospatial Engineering and Science, Sun Yat-sen University, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 51908, China
Key Laboratory of Comprehensive Observation of Polar Environment (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
Xiao Cheng
CORRESPONDING AUTHOR
School of Geospatial Engineering and Science, Sun Yat-sen University, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 51908, China
Key Laboratory of Comprehensive Observation of Polar Environment (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK
State Key Laboratory of Remote Sensing and Digital Earth, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
School of Geospatial Engineering and Science, Sun Yat-sen University, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 51908, China
Key Laboratory of Comprehensive Observation of Polar Environment (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
Lei Zheng
School of Geospatial Engineering and Science, Sun Yat-sen University, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 51908, China
Key Laboratory of Comprehensive Observation of Polar Environment (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
Jiping Liu
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 51908, China
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Linlu Mei, Vladimir Rozanov, Evelyn Jäkel, Xiao Cheng, Marco Vountas, and John P. Burrows
The Cryosphere, 15, 2781–2802, https://doi.org/10.5194/tc-15-2781-2021, https://doi.org/10.5194/tc-15-2781-2021, 2021
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This paper presents a new snow property retrieval algorithm from satellite observations. This is Part 2 of two companion papers and shows the results and validation. The paper performs the new retrieval algorithm on the Sea and Land
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Yu Zhou, Jianlong Chen, and Xiao Cheng
Earth Surf. Dynam. Discuss., https://doi.org/10.5194/esurf-2021-21, https://doi.org/10.5194/esurf-2021-21, 2021
Preprint withdrawn
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Short summary
Our study uses Google Earth Engine to create a dataset of Antarctic icebergs in the Southern Ocean (south of 55° S) from October 2018 to 2023. The dataset includes icebergs larger than 0.04 km², with details on their locations, sizes, and shapes. It shows significant changes in iceberg number and area, mainly driven by major ice shelf calving events – especially in the Weddell Sea. This resource fills key gaps in understanding iceberg impacts on the ocean and climate.
Our study uses Google Earth Engine to create a dataset of Antarctic icebergs in the Southern...
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