Articles | Volume 17, issue 1
https://doi.org/10.5194/essd-17-205-2025
© Author(s) 2025. 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-17-205-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
24 Jan 2025
Data description paper |
| 24 Jan 2025
| 24 Jan 2025
Global digital elevation model (GDEM) product generation by correcting ASTER GDEM elevation with ICESat-2 altimeter data
Binbin Li
College of Surveying and Geo-informatics, and Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, China
JC STEM Lab of Earth Observations, Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR 999077, China
Research Centre for Artificial Intelligence in Geomatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR 999077, China
Research Institute for Land and Space, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR 999077, China
College of Surveying and Geo-informatics, and Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, China
Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 200092, China
Shijie Liu
College of Surveying and Geo-informatics, and Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, China
Zhen Ye
College of Surveying and Geo-informatics, and Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, China
Zhonghua Hong
College of Information Technology, Shanghai Ocean University, Shanghai 201306, China
Qihao Weng
JC STEM Lab of Earth Observations, Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR 999077, China
Research Centre for Artificial Intelligence in Geomatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR 999077, China
Research Institute for Land and Space, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR 999077, China
Yuan Sun
College of Surveying and Geo-informatics, and Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, China
Qi Xu
College of Surveying and Geo-informatics, and Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, China
Xiaohua Tong
College of Surveying and Geo-informatics, and Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, China
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-3-2024, 629–635, https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-629-2024, https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-629-2024, 2024
Jiarui Cao, Rong Huang, Zhen Ye, Yusheng Xu, and Xiaohua Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-3-2024, 51–56, https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-51-2024, https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-51-2024, 2024
Ying Tu, Shengbiao Wu, Bin Chen, Qihao Weng, Yuqi Bai, Jun Yang, Le Yu, and Bing Xu
Earth Syst. Sci. Data, 16, 2297–2316, https://doi.org/10.5194/essd-16-2297-2024, https://doi.org/10.5194/essd-16-2297-2024, 2024
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We developed the first 30 m annual cropland dataset of China (CACD) for 1986–2021. The overall accuracy of CACD reached up to 0.93±0.01 and was superior to other products. Our fine-resolution cropland maps offer valuable information for diverse applications and decision-making processes in the future.
Xin Luo, Hongping Zeng, and Zhen Ye
EGUsphere, https://doi.org/10.5194/egusphere-2023-2389, https://doi.org/10.5194/egusphere-2023-2389, 2023
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To better understand the glacier melting features in the SETP, multisource satellite observations including ASTER DEM, ICESat, ICESat-2 and CryoSat-2 are used in this study. We found the glacier melting rate of the entire SETP is during 2000–2022. And the glacier melting has accelerated at a rate of 31.2 % in the recent decade. A comprehensive comparison among the related existing studies revealed that our estimates have a finer temporal scale and less estimation uncertainty.
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
Lixin Lin, Xixi Liu, and Yuan Sun
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-170, https://doi.org/10.5194/bg-2023-170, 2023
Revised manuscript not accepted
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We attempted to disentangle the covers of vegetation and water on soil organic carbon model using fuzzy disentangling. We used the model to simulate the soil organic carbon stocks in western European topsoil. The results show that the per-unit and total SOC stocks in western European topsoil as 99.742 t C ha−1 and 9.373 Pg, respectively. The gap of the results is narrower compared with previous study. The stable simulated values are the result of disentangling of the vegetation and water cover.
Yuelong Xiao, Qunming Wang, Xiaohua Tong, and Peter M. Atkinson
Earth Syst. Sci. Data, 15, 3365–3386, https://doi.org/10.5194/essd-15-3365-2023, https://doi.org/10.5194/essd-15-3365-2023, 2023
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Forest age is closely related to forest production, carbon cycles, and other ecosystem services. Existing stand age products in China derived from remote-sensing images are of a coarse spatial resolution and are not suitable for applications at the regional scale. Here, we mapped young forest ages across China at an unprecedented fine spatial resolution of 30 m. The overall accuracy (OA) of the generated map of young forest stand ages across China was 90.28 %.
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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
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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
H. Zhang, Y. Shang, X. Tong, J. Chen, W. Ma, M. Li, Y. Lu, and H. Chen
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 619–625, https://doi.org/10.5194/isprs-annals-V-3-2022-619-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-619-2022, 2022
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The Cryosphere, 15, 3083–3099, https://doi.org/10.5194/tc-15-3083-2021, https://doi.org/10.5194/tc-15-3083-2021, 2021
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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.
H. Cui, R. Li, H. Li, T. Hao, G. Qiao, Y. He, G. Hai, H. Xie, Y. Cheng, and B. Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 443–448, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-443-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-443-2021, 2021
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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
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ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2020, 17–23, https://doi.org/10.5194/isprs-annals-V-1-2020-17-2020, https://doi.org/10.5194/isprs-annals-V-1-2020-17-2020, 2020
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ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 235–242, https://doi.org/10.5194/isprs-annals-V-2-2020-235-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-235-2020, 2020
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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
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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
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Y. Lu, J. Zhang, X. Tong, W. Han, and H. Zhao
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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
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Z. Ye, Y. Xu, L. Hoegner, X. Tong, and U. Stilla
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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
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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
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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
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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
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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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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.
We refined the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital...
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