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ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume V-3-2020
https://doi.org/10.5194/isprs-annals-V-3-2020-141-2020
© Author(s) 2020. 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-annals-V-3-2020-141-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
03 Aug 2020
| 03 Aug 2020
SELECTION OF PERSISTENT SCATTERER INTERFEROMETRIC SYNTHETIC APERTURE RADAR MASTER IMAGE CONSIDERING TEMPORAL BASELINE, SPATIAL BASELINE AND DOPPLER CENTROID FREQUENCY DIFFERENCE
Y. Lu
School of Surveying and Geo-Informatics, Tongji University, Shanghai, China
National Quality Inspection and Testing Center For Surveying and Mapping Products, Beijing, China
J. Zhang
National Quality Inspection and Testing Center For Surveying and Mapping Products, Beijing, China
X. Tong
School of Surveying and Geo-Informatics, Tongji University, Shanghai, China
X. Lu
Key Laboratory of Spatio-Temporal Information and Ecological Restoration of Mines, Ministry of Natural Resources of the People's Republic of China, Henan Polytechnic University, Jiaozuo, China
W. Han
National Quality Inspection and Testing Center For Surveying and Mapping Products, Beijing, China
H. Zhang
National Quality Inspection and Testing Center For Surveying and Mapping Products, Beijing, China
H. Zhao
National Quality Inspection and Testing Center For Surveying and Mapping Products, Beijing, China
X. Liu
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 749–754, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-749-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-749-2021, 2021
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 811–816, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-811-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-811-2021, 2021
S. Luo, Y. Cheng, Z. Li, Y. Wang, K. Wang, X. Wang, G. Qiao, W. Ye, Y. Li, M. Xia, X. Yuan, Y. Tian, X. Tong, and R. Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 491–496, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-491-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-491-2021, 2021
Y. Gong, H. Xie, X. Tong, Y. Jin, X. Xv, and Q. Wang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2020, 103–108, https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-103-2020, https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-103-2020, 2020
W. C. Gao, H. T. Zhao, W. J. Mao, S. Yin, and Z. B. Tian
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1327–1331, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1327-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1327-2020, 2020
J. Guo, J. X. Zhang, H. T. Zhao, C. Li, J. Zhou, H. J. Tu, and Y. Zhao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1333–1338, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1333-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1333-2020, 2020
Y. Zhao, H. T. Zhao, J. Guo, H. J. Tu, and S. Yin
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1411–1416, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1411-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1411-2020, 2020
X. Liu, X. Lu, and L. Ma
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 319–323, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-319-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-319-2020, 2020
X. Zhang, Y. Yang, J. Zhang, J. Liu, and M. Wan
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1505–1511, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1505-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1505-2020, 2020
H. Zhang, S. Liu, Z. Ye, X. Tong, H. Xie, S. Zheng, and Q. Du
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 149–155, https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-149-2020, https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-149-2020, 2020
Z. Ye, Y. Xu, C. Wei, X. Tong, and U. Stilla
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2020, 157–163, https://doi.org/10.5194/isprs-annals-V-1-2020-157-2020, https://doi.org/10.5194/isprs-annals-V-1-2020-157-2020, 2020
Y. Zhou, X. Lu, Y. Huang, Z. Gao, and Y. Zheng
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 209–214, https://doi.org/10.5194/isprs-annals-V-3-2020-209-2020, https://doi.org/10.5194/isprs-annals-V-3-2020-209-2020, 2020
Y. Wang, X. Tong, H. Xie, M. Jiang, Y. Huang, S. Liu, X. Xu, Q. Du, Q. Wang, and C. Wang
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 603–608, https://doi.org/10.5194/isprs-annals-V-3-2020-603-2020, https://doi.org/10.5194/isprs-annals-V-3-2020-603-2020, 2020
Q. Fu, S. Liu, X. Tong, and H. Wang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W16, 91–94, https://doi.org/10.5194/isprs-archives-XLII-2-W16-91-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W16-91-2019, 2019
S. Gao, Z. Ye, C. Wei, X. Liu, and X. Tong
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 33–38, https://doi.org/10.5194/isprs-annals-IV-2-W7-33-2019, https://doi.org/10.5194/isprs-annals-IV-2-W7-33-2019, 2019
Y. Lu, J. Zhang, X. Tong, W. Han, and H. Zhao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1243–1247, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1243-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1243-2019, 2019
X. Zhang, X. Zhang, and H. Zhang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1369–1374, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1369-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1369-2019, 2019
Y. Cheng, X. Li, G. Qiao, W. Ye, Y. Huang, Y. Li, K. Wang, Y. Tian, X. Tong, and R. Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1735–1739, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1735-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1735-2019, 2019
R. Li, D. Lv, H. Xiao, S. Liu, Y. Cheng, G. Hai, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1759–1763, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1759-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1759-2019, 2019
R. Li, H. Xie, Y. Tian, W. Du, J. Chen, G. Hai, S. Zhang, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1765–1769, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1765-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1765-2019, 2019
Z. Ye, Y. Xu, L. Hoegner, X. Tong, and U. Stilla
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 147–153, https://doi.org/10.5194/isprs-archives-XLII-2-W13-147-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-147-2019, 2019
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
Wenping Song, Shijie Liu, Xiaohua Tong, Changling Niu, Zhen Ye, Han Zhang, and Yanmin Jin
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 193–196, https://doi.org/10.5194/isprs-annals-IV-3-193-2018, https://doi.org/10.5194/isprs-annals-IV-3-193-2018, 2018
Xin Zhang, Shijie Liu, Haifeng Yu, Xiaohua Tong, and Guoman Huang
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 267–271, https://doi.org/10.5194/isprs-annals-IV-3-267-2018, https://doi.org/10.5194/isprs-annals-IV-3-267-2018, 2018
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
M. Xia, G. Tang, Y. Tian, W. Ye, R. Li, and X. Tong
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
H. Xiao, S. Liu, R. Li, and X. Tong
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
Rongxing Li, Haifeng Xiao, Shijie Liu, and Xiaohua Tong
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-178, https://doi.org/10.5194/tc-2017-178, 2017
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.
C. Guo, X. Tong, S. Liu, S. Liu, X. Lu, P. Chen, Y. Jin, and H. Xie
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W1, 49–53, https://doi.org/10.5194/isprs-archives-XLII-3-W1-49-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W1-49-2017, 2017
W. Zhao, X. Tong, H. Xie, Y. Jin, S. Liu, D. Wu, X. Liu, L. Guo, and Q. Zhou
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W1, 213–218, https://doi.org/10.5194/isprs-archives-XLII-3-W1-213-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W1-213-2017, 2017
Q. Zhou, X. Tong, S. Liu, X. Lu, S. Liu, P. Chen, Y. Jin, and H. Xie
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W1, 219–224, https://doi.org/10.5194/isprs-archives-XLII-3-W1-219-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W1-219-2017, 2017
W. Cao, X. H. Tong, S. C. Liu, and D. Wang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 25–31, https://doi.org/10.5194/isprs-archives-XLI-B8-25-2016, https://doi.org/10.5194/isprs-archives-XLI-B8-25-2016, 2016
T. Feng, Z. Hong, Q. Fu, S. Ma, X. Jie, H. Wu, C. Jiang, and X. Tong
Nat. Hazards Earth Syst. Sci., 14, 2165–2178, https://doi.org/10.5194/nhess-14-2165-2014, https://doi.org/10.5194/nhess-14-2165-2014, 2014
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