- Article
(1079 KB) - Metadata XML
- August 09, 2025
- |
- Home
- |
- Sitemap
- |
- The ISPRS Foundation
- |
- 𝕏
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
Related authors
S. Ge, Y. Cheng, R. Li, H. Cui, Z. Yu, T. Chang, S. Luo, Z. Li, G. Li, A. Zhao, X. Yuan, Y. Li, M. Xia, X. Wang, and G. Qiao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 757–763, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-757-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-757-2022, 2022
Rongxing Li, Yuan Cheng, Haotian Cui, Menglian Xia, Xiaohan Yuan, Zhen Li, Shulei Luo, and Gang Qiao
The Cryosphere, 16, 737–760, https://doi.org/10.5194/tc-16-737-2022, https://doi.org/10.5194/tc-16-737-2022, 2022
Short summary
Short summary
Historical velocity maps of the Antarctic ice sheet are valuable for long-term ice flow dynamics analysis. We developed an innovative method for correcting overestimations existing in historical velocity maps. The method is validated rigorously using high-quality Landsat 8 images and then successfully applied to historical velocity maps. The historical change signatures are preserved and can be used for assessing the impact of long-term global climate changes on the ice sheet.
Rongxing Li, Hongwei Li, Tong Hao, Gang Qiao, Haotian Cui, Youquan He, Gang Hai, Huan Xie, Yuan Cheng, and Bofeng Li
The Cryosphere, 15, 3083–3099, https://doi.org/10.5194/tc-15-3083-2021, https://doi.org/10.5194/tc-15-3083-2021, 2021
Short summary
Short summary
We present the results of an assessment of ICESat-2 surface elevations along the 520 km CHINARE route in East Antarctica. The assessment was performed based on coordinated multi-sensor observations from a global navigation satellite system, corner cube retroreflectors, retroreflective target sheets, and UAVs. The validation results demonstrate that ICESat-2 elevations are accurate to 1.5–2.5 cm and can potentially overcome the uncertainties in the estimation of mass balance in East Antarctica.
Huan Xie, Yifan Wang, Xiongfeng Yan, Ming Yang, Yaqiong Wang, and Xiaohua Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-G-2025, 1589–1594, https://doi.org/10.5194/isprs-archives-XLVIII-G-2025-1589-2025, https://doi.org/10.5194/isprs-archives-XLVIII-G-2025-1589-2025, 2025
Yuan Sun, Huan Xie, Xiaohua Tong, Qi Xu, Binbin Li, Changda Liu, Min Ji, and Hao Tang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-G-2025, 1421–1426, https://doi.org/10.5194/isprs-archives-XLVIII-G-2025-1421-2025, https://doi.org/10.5194/isprs-archives-XLVIII-G-2025-1421-2025, 2025
Chen Liu, Rong Huang, Huan Xie, Tao Tao, Yongjiu Feng, and Xiaohua Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-G-2025, 959–966, https://doi.org/10.5194/isprs-archives-XLVIII-G-2025-959-2025, https://doi.org/10.5194/isprs-archives-XLVIII-G-2025-959-2025, 2025
Tiantian Feng, Hui Dong, Yangyang Chen, and Tong Hao
EGUsphere, https://doi.org/10.5194/egusphere-2025-1632, https://doi.org/10.5194/egusphere-2025-1632, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
This study focuses on the long-term subglacial hydrological activity of the Recovery Ice Stream in East Antarctica. We update the outlines of reported lakes based on their recent activity and identify 14 new lakes. A 21-year record of elevation changes of these lakes is constructed using multi-mission altimetry data. We also reveal spatial variability in elevation change patterns within several typical individual lakes. Our hydrological network confirms hydraulic connectivity among these lakes.
Zhilu Wu, Bofeng Li, Qingyuan Liu, Yanxiong Liu, Huayi Zhang, Dongxu Zhou, and Yang Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-24, https://doi.org/10.5194/essd-2025-24, 2025
Revised manuscript under review for ESSD
Short summary
Short summary
We created a reliable dataset of atmospheric water vapor from China's coastal stations (2009–2019), validated against global models and radiosonde data. The study highlights strong links between water vapor and sea surface temperature, aiding understanding of weather, extreme events, and climate change. This dataset supports improved forecasting and climate research.
Menglian Xia, Rongxing Li, Marco Scaioni, Lu An, Zhenshi Li, and Gang Qiao
EGUsphere, https://doi.org/10.5194/egusphere-2025-175, https://doi.org/10.5194/egusphere-2025-175, 2025
Short summary
Short summary
We propose an innovative multi-satellite DEM adjustment model (MDAM) that removes biases in elevation between sub-DEMs across ice shelves. Our results reveal quantitative 3D structural and mélange features of a ~50 km long rift. For first time, we found that while the mélange elevation decreased from 2014–2021, the mélange inside the rift experienced a rapid expansion, attributing to newly calved shelf ice from rift walls, associated rift widening, and other rift-mélange interaction factors.
Binbin Li, Huan Xie, Shijie Liu, Zhen Ye, Zhonghua Hong, Qihao Weng, Yuan Sun, Qi Xu, and Xiaohua Tong
Earth Syst. Sci. Data, 17, 205–220, https://doi.org/10.5194/essd-17-205-2025, https://doi.org/10.5194/essd-17-205-2025, 2025
Short summary
Short summary
We refined the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) with Ice, Cloud, and Land Elevation Satellite 2 data to release a new dataset (IC2-GDEM). It has superior global elevation quality to ASTER GDEM. Its seamless integration with historical ASTER GDEM datasets is essential for longitudinal environmental studies. As a complementary data source to other GDEMs, it enables more reliable and comprehensive scientific discoveries.
Litao Dai, Xingchen Liu, Lu An, and Rongxing Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-3-2024, 101–106, https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-101-2024, https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-101-2024, 2024
Penglan Luo, Gang Qiao, Zhi Qu, and Sergey Popov
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-3-2024, 311–318, https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-311-2024, https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-311-2024, 2024
Chengjin Yan, Yuan Cheng, Yue Zhang, Haomin Yu, Jizhong Huang, and Hongbin Yan
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-2024, 541–547, https://doi.org/10.5194/isprs-archives-XLVIII-4-2024-541-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-2024-541-2024, 2024
Yanjun Li, Violaine Coulon, Javier Blasco, Gang Qiao, Qinghua Yang, and Frank Pattyn
EGUsphere, https://doi.org/10.5194/egusphere-2024-2916, https://doi.org/10.5194/egusphere-2024-2916, 2024
Short summary
Short summary
We incorporate ice damage processes into an ice-sheet model and apply the new model to Thwaites Glacier. The upgraded model more accurately captures the observed ice geometry and mass balance of Thwaites Glacier over 1990–2020. Our simulations show that ice damage has a notable impact on the ice sheet evolution, ice mass loss and the resulted sea-level rise. This study highlights the necessity for incorporating ice damage into ice-sheet models.
Xiaofeng Wang, Lu An, Peter L. Langen, and Rongxing Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-2024, 691–696, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-691-2024, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-691-2024, 2024
Xin Wang, Yuan Cheng, Ruoyu Zhang, Yue Zhang, Jizhong Huang, and Hongbin Yan
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-2024, 713–719, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-713-2024, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-713-2024, 2024
Zheyi Cao, Leyue Tang, Xiaohan Yuan, and Gang Qiao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-2024, 59–64, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-59-2024, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-59-2024, 2024
Hongwei Li, Youquan He, Yuanyuan Gu, and Gang Qiao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-2024, 323–328, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-323-2024, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-323-2024, 2024
Y. Cheng, J. Xue, H. Yu, and G. Hai
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W9-2024, 99–105, https://doi.org/10.5194/isprs-archives-XLVIII-4-W9-2024-99-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W9-2024-99-2024, 2024
S. Xu, R. Huang, Y. Xu, Z. Ye, H. Xie, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 771–776, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-771-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-771-2023, 2023
Q. Xu, H. Xie, Y. Sun, X. Liu, Y. Guo, P. Huang, B. Li, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 309–314, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-309-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-309-2022, 2022
S. Ge, Y. Cheng, R. Li, H. Cui, Z. Yu, T. Chang, S. Luo, Z. Li, G. Li, A. Zhao, X. Yuan, Y. Li, M. Xia, X. Wang, and G. Qiao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 757–763, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-757-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-757-2022, 2022
K. Lin, G. Qiao, L. Zhang, and S. Popov
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 765–770, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-765-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-765-2022, 2022
L. Wang, G. Qiao, I. V. Florinsky, and S. Popov
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 785–791, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-785-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-785-2022, 2022
Z. Yu, Z. Cao, C. Yu, G. Qiao, and R. Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 799–804, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-799-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-799-2022, 2022
A. Zhao, Y. Cheng, D. Lv, M. Xia, R. Li, L. An, S. Liu, and Y. Tian
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 805–811, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-805-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-805-2022, 2022
Rongxing Li, Yuan Cheng, Haotian Cui, Menglian Xia, Xiaohan Yuan, Zhen Li, Shulei Luo, and Gang Qiao
The Cryosphere, 16, 737–760, https://doi.org/10.5194/tc-16-737-2022, https://doi.org/10.5194/tc-16-737-2022, 2022
Short summary
Short summary
Historical velocity maps of the Antarctic ice sheet are valuable for long-term ice flow dynamics analysis. We developed an innovative method for correcting overestimations existing in historical velocity maps. The method is validated rigorously using high-quality Landsat 8 images and then successfully applied to historical velocity maps. The historical change signatures are preserved and can be used for assessing the impact of long-term global climate changes on the ice sheet.
Lin Li, Aiguo Zhao, Tiantian Feng, Xiangbin Cui, Lu An, Ben Xu, Shinan Lang, Liwen Jing, Tong Hao, Jingxue Guo, Bo Sun, and Rongxing Li
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-332, https://doi.org/10.5194/tc-2021-332, 2021
Preprint withdrawn
Short summary
Short summary
No subglacial lakes have been reported in Princess Elizabeth Land (PEL), East Antarctica. In this study, thanks to a new suite of airborne geophysical observations in PEL, including RES and gravity data collected during the Chinese National Antarctic Research Expedition, we detected a large subglacial lake of ~45 km in length, ~11 km in width, and ~250 m in depth. These findings will help us understand ice sheet stability in the PEL region.
Rongxing Li, Hongwei Li, Tong Hao, Gang Qiao, Haotian Cui, Youquan He, Gang Hai, Huan Xie, Yuan Cheng, and Bofeng Li
The Cryosphere, 15, 3083–3099, https://doi.org/10.5194/tc-15-3083-2021, https://doi.org/10.5194/tc-15-3083-2021, 2021
Short summary
Short summary
We present the results of an assessment of ICESat-2 surface elevations along the 520 km CHINARE route in East Antarctica. The assessment was performed based on coordinated multi-sensor observations from a global navigation satellite system, corner cube retroreflectors, retroreflective target sheets, and UAVs. The validation results demonstrate that ICESat-2 elevations are accurate to 1.5–2.5 cm and can potentially overcome the uncertainties in the estimation of mass balance in East Antarctica.
T. Chang, J. Han, Z. Li, Y. Wen, T. Hao, P. Lu, and R. Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 437–442, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-437-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-437-2021, 2021
Y. He, G. Qiao, H. Li, X. Yuan, and Y. Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 463–468, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-463-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-463-2021, 2021
Y. Li, G. Qiao, and X. Yuan
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 485–490, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-485-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-485-2021, 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
Z. Sun and G. Qiao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 503–508, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-503-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-503-2021, 2021
D. Wang, T. Feng, T. Hao, and R. Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 521–526, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-521-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-521-2021, 2021
H. Zhao, R. Xu, and G. Qiao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 527–532, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-527-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-527-2021, 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
X. Yuan, G. Qiao, Y. Li, H. Li, and R. Xu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 919–923, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-919-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-919-2020, 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
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
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
R. G. Xu, G. Qiao, Y. J. Wu, and Y. J. Cao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1797–1801, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1797-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1797-2019, 2019
L. Liu, B. Li, S. Zlatanova, and H. Liu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 373–378, https://doi.org/10.5194/isprs-archives-XLII-4-373-2018, https://doi.org/10.5194/isprs-archives-XLII-4-373-2018, 2018
X. Li, R. Li, G. Qiao, Y. Cheng, W. Ye, T. Gao, Y. Huang, Y. Tian, and X. Tong
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
Y. J. Cao and G. Qiao
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
Y. J. Li and G. Qiao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1541–1546, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1541-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1541-2017, 2017
Y. J. Wu, G. Qiao, and H. W. Li
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
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.
R. Li, W. Ye, F. Kong, G. Qiao, X. Tong, X. Ma, S. Guo, and Z. Wang
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.
Useful Links
Useful External Links
Our Contact
c/o
Leibniz University Hannover
Institute of Photogrammetry and GeoInformation
Nienburger Str. 1
D-30167 Hannover
GERMANY
Email: isprs-sg@isprs.org