Articles | Volume 15, issue 10
https://doi.org/10.5194/tc-15-4727-2021
© 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-15-4727-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Oct 2021
Research article |
| 07 Oct 2021
| 07 Oct 2021
Semi-automated tracking of iceberg B43 using Sentinel-1 SAR images via Google Earth Engine
YoungHyun Koo
Center for Advanced Measurements in Extreme Environments, University of Texas at San Antonio, San Antonio, TX 78249, USA
Hongjie Xie
CORRESPONDING AUTHOR
Center for Advanced Measurements in Extreme Environments, University of Texas at San Antonio, San Antonio, TX 78249, USA
Stephen F. Ackley
Center for Advanced Measurements in Extreme Environments, University of Texas at San Antonio, San Antonio, TX 78249, USA
Alberto M. Mestas-Nuñez
Center for Advanced Measurements in Extreme Environments, University of Texas at San Antonio, San Antonio, TX 78249, USA
Grant J. Macdonald
Center for Advanced Measurements in Extreme Environments, University of Texas at San Antonio, San Antonio, TX 78249, USA
Chang-Uk Hyun
Department of Energy and Mineral Resources Engineering, Dong-A
University, Busan 49315, Republic of Korea
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Short summary
This study demonstrates for the first time the potential of Google Earth Engine (GEE) cloud-computing platform and Sentinel-1 synthetic aperture radar (SAR) images for semi-automated tracking of area changes and movements of iceberg B43. Our novel GEE-based iceberg tracking can be used to construct a large iceberg database for a better understanding of the behavior of icebergs and their interactions with surrounding environments.
This study demonstrates for the first time the potential of Google Earth Engine (GEE)...
