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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLIII-B3-2021
https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-443-2021
© 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/isprs-archives-XLIII-B3-2021-443-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
28 Jun 2021
| 28 Jun 2021
FIELD VALIDATION OF ICESAT-2 DATA ALONG CHINARE ROUTE IN EAST ANTARCTICA
H. Cui
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, 1239 Siping Road, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, 1239 Siping Road, Shanghai, China
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, 1239 Siping Road, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, 1239 Siping Road, Shanghai, China
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, 1239 Siping Road, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, 1239 Siping Road, Shanghai, China
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, 1239 Siping Road, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, 1239 Siping Road, Shanghai, China
G. Qiao
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, 1239 Siping Road, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, 1239 Siping Road, Shanghai, China
Y. He
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, 1239 Siping Road, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, 1239 Siping Road, Shanghai, China
G. Hai
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, 1239 Siping Road, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, 1239 Siping Road, Shanghai, China
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, 1239 Siping Road, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, 1239 Siping Road, Shanghai, China
Y. Cheng
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, 1239 Siping Road, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, 1239 Siping Road, Shanghai, China
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, 1239 Siping Road, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, 1239 Siping Road, Shanghai, China
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Y. Wang, X. Tong, H. Xie, M. Jiang, Y. Huang, S. Liu, X. Xu, Q. Du, Q. Wang, and C. Wang
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R. Li, D. Lv, H. Xiao, S. Liu, Y. Cheng, G. Hai, and X. Tong
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R. Li, H. Xie, Y. Tian, W. Du, J. Chen, G. Hai, S. Zhang, and X. Tong
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 2625–2628, https://doi.org/10.5194/isprs-archives-XLII-3-2625-2018, https://doi.org/10.5194/isprs-archives-XLII-3-2625-2018, 2018
Y. Tian, S. Zhang, W. Du, J. Chen, H. Xie, X. Tong, and R. Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1657–1660, https://doi.org/10.5194/isprs-archives-XLII-3-1657-2018, https://doi.org/10.5194/isprs-archives-XLII-3-1657-2018, 2018
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1503–1507, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1503-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1503-2017, 2017
L. M. Chen, G. Qiao, and P. Lu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1509–1512, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1509-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1509-2017, 2017
W. Du, L. Chen, H. Xie, G. Hai, S. Zhang, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1513–1516, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1513-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1513-2017, 2017
G. Hai, H. Xie, J. Chen, L. Chen, R. Li, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1517–1520, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1517-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1517-2017, 2017
H. W. Li, G. Qiao, Y. J. Wu, Y. J. Cao, and H. Mi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1529–1533, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1529-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1529-2017, 2017
R. Li, X. Ma, Y. Cheng, W. Ye, S. Guo, G. Tang, Z. Wang, T. Gao, Y. Huang, X. Li, G. Qiao, Y. Tian, T. Feng, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1535–1539, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1535-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1535-2017, 2017
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1555–1560, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1555-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1555-2017, 2017
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1569–1573, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1569-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1569-2017, 2017
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1575–1577, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1575-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1575-2017, 2017
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Revised manuscript not accepted
Short summary
Short summary
Fracturing in the RFIS was slightly increased, particularly at its front, from 2003 to 2015. They do not seem to suggest an immediate significant impact on the stability of the shelf. However, with the rapid changes and 3D measurements of Rifts 1 and 2, the most active activities occurred at the front of the FIS from 2001 to 2016. A potential upcoming major calving event in FIS is estimated to occur in 2051. The stability of the ice shelf, particularly Rifts 1 and 2, should be closely monitored.
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 521–524, https://doi.org/10.5194/isprs-archives-XLI-B8-521-2016, https://doi.org/10.5194/isprs-archives-XLI-B8-521-2016, 2016
Huan Xie, Gang Hai, Lei Chen, Shijie Liu, Jun Liu, Xiaohua Tong, and Rongxing Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 549–553, https://doi.org/10.5194/isprs-archives-XLI-B8-549-2016, https://doi.org/10.5194/isprs-archives-XLI-B8-549-2016, 2016
The International Society for Photogrammetry and Remote Sensing is a non-governmental organization devoted to the development of international cooperation for the advancement of photogrammetry and remote sensing and their applications. The Society operates without any discrimination on grounds of race, religion, nationality, or political philosophy.
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