Articles | Volume 17, issue 9
https://doi.org/10.5194/essd-17-4397-2025
© 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-17-4397-2025
© 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
| 
08 Sep 2025
Data description paper |
| 08 Sep 2025
| 08 Sep 2025
Large-scale forest stand height mapping in the northeastern US and China using L-band spaceborne repeat-pass InSAR and GEDI lidar data
Yanghai Yu
National Space Science Center, Chinese Academy of Sciences, Beijing, 100190, China
National Space Science Center, Chinese Academy of Sciences, Beijing, 100190, China
Paul Siqueira
Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA 01003-9284, USA
Xiaotong Liu
Academy of Forest Inventory and Planning, State Forestry Administration, Beijing, 100714, China
Denuo Gu
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, China
Anmin Fu
Academy of Forest Inventory and Planning, State Forestry Administration, Beijing, 100714, China
Yong Pang
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, China
Wenli Huang
School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, China
Jiancheng Shi
National Space Science Center, Chinese Academy of Sciences, Beijing, 100190, China
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The Cryosphere, 19, 3517–3533, https://doi.org/10.5194/tc-19-3517-2025, https://doi.org/10.5194/tc-19-3517-2025, 2025
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The NASA MEaSUREs Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) project provides glacier and ice sheet velocity products for the full Landsat, Sentinel-1, and Sentinel-2 satellite archives and will soon include data from the NISAR satellite. This paper describes the ITS_LIVE processing chain and gives guidance for working with the cloud-optimized glacier and ice sheet velocity products.
Qixiang Sun, Dabin Ji, Husi Letu, Yongqian Wang, Peng Zhang, Hong Liang, Chong Shi, Shuai Yin, and Jiancheng Shi
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-365, https://doi.org/10.5194/essd-2025-365, 2025
Preprint under review for ESSD
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The Tibetan Plateau plays a vital role in Asia’s water cycle, but tracking water vapor in this mountainous region is difficult, especially under cloudy conditions. We developed a new satellite-based method to generate hourly water vapor data at 0.02-degree resolution from 2016 to 2022, now available at https://data.tpdc.ac.cn/en/data/4bb3c256-3cdb-4373-9924-f7ac16ddc717, which improves accuracy and reveals fine-scale moisture transport critical for understanding rainfall and extreme weather.
Jingtian Zhou, Yang Lei, Jinmei Pan, Cunren Liang, Yunjun Zhang, Weiliang Li, Chuan Xiong, and Jiancheng Shi
EGUsphere, https://doi.org/10.5194/egusphere-2025-2329, https://doi.org/10.5194/egusphere-2025-2329, 2025
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Understanding how much water is stored in snow is important for tracking climate change and managing water supply. This study used satellite radar data from 2019 to 2021 to measure snow water changes in a mountain region of China. The results matched ground data well, especially in cold, dry conditions without heavy snowfall. A new phase calibration method helped improve accuracy, offering a useful reference for global snow monitoring using widely available satellite data.
Benoit Montpetit, Julien Meloche, Vincent Vionnet, Chris Derksen, Georgina Wooley, Nicolas R. Leroux, Paul Siqueira, J. Max Adams, and Mike Brady
EGUsphere, https://doi.org/10.5194/egusphere-2025-2317, https://doi.org/10.5194/egusphere-2025-2317, 2025
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This paper presents the workflow to retrieve snow water equivalent from radar measurements for the future Canadian radar satellite mission, TSMM. The workflow is validated by using airborne radar data collected at Trail Valley Creek, Canada, during winter 2018–19. We detail important considerations to have in the context of an Earth Observation mission over a vast region such as Canada. The results show that it is possible to achieve the desired accuracy for TSMM, over an Arctic environment.
Defeng Feng, Tianjie Zhao, Jingyao Zheng, Yu Bai, Youhua Ran, Xiaokang Kou, Lingmei Jiang, Ziqian Zhang, Pei Yu, Jinbiao Zhu, Jie Pan, Jiancheng Shi, and Yuei-An Liou
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-62, https://doi.org/10.5194/essd-2025-62, 2025
Revised manuscript accepted for ESSD
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This study introduces a downscaling approach that integrates passive microwave and optical satellite data to generate a long-term (2002–2023), high-resolution (0.05°) global near-surface FT state dataset, ensuring daily seamless continuity. The dataset achieves an overall accuracy of 83.78%, consistent with the microwave-based dataset while offering enhanced spatial detail. This record providing detailed FT information, enhancing the understanding of hydrological and ecological impacts globally.
Benoit Montpetit, Joshua King, Julien Meloche, Chris Derksen, Paul Siqueira, J. Max Adam, Peter Toose, Mike Brady, Anna Wendleder, Vincent Vionnet, and Nicolas R. Leroux
The Cryosphere, 18, 3857–3874, https://doi.org/10.5194/tc-18-3857-2024, https://doi.org/10.5194/tc-18-3857-2024, 2024
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Fangbo Pan, Lingmei Jiang, Gongxue Wang, Jinmei Pan, Jinyu Huang, Cheng Zhang, Huizhen Cui, Jianwei Yang, Zhaojun Zheng, Shengli Wu, and Jiancheng Shi
Earth Syst. Sci. Data, 16, 2501–2523, https://doi.org/10.5194/essd-16-2501-2024, https://doi.org/10.5194/essd-16-2501-2024, 2024
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It is important to strengthen the continuous monitoring of snow cover as a key indicator of imbalance in the Asian Water Tower (AWT) region. We generate long-term daily gap-free fractional snow cover products over the AWT at 0.005° resolution from 2000 to 2022 based on the multiple-endmember spectral mixture analysis algorithm and the gap-filling algorithm. They can provide highly accurate, quantitative fractional snow cover information for subsequent studies on hydrology and climate.
Jinmei Pan, Michael Durand, Juha Lemmetyinen, Desheng Liu, and Jiancheng Shi
The Cryosphere, 18, 1561–1578, https://doi.org/10.5194/tc-18-1561-2024, https://doi.org/10.5194/tc-18-1561-2024, 2024
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We developed an algorithm to estimate snow mass using X- and dual Ku-band radar, and tested it in a ground-based experiment. The algorithm, the Bayesian-based Algorithm for SWE Estimation (BASE) using active microwaves, achieved an RMSE of 30 mm for snow water equivalent. These results demonstrate the potential of radar, a highly promising sensor, to map snow mass at high spatial resolution.
Yang Lei, Alex S. Gardner, and Piyush Agram
Earth Syst. Sci. Data, 14, 5111–5137, https://doi.org/10.5194/essd-14-5111-2022, https://doi.org/10.5194/essd-14-5111-2022, 2022
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This work describes NASA MEaSUREs ITS_LIVE project's Version 2 Sentinel-1 image-pair ice velocity product and processing methodology. We show the refined offset tracking algorithm, autoRIFT, calibration for Sentinel-1 geolocation biases and correction of the ionosphere streaking problems. Validation was performed over three typical test sites covering the globe by comparing with other similar global and regional products.
Leung Tsang, Michael Durand, Chris Derksen, Ana P. Barros, Do-Hyuk Kang, Hans Lievens, Hans-Peter Marshall, Jiyue Zhu, Joel Johnson, Joshua King, Juha Lemmetyinen, Melody Sandells, Nick Rutter, Paul Siqueira, Anne Nolin, Batu Osmanoglu, Carrie Vuyovich, Edward Kim, Drew Taylor, Ioanna Merkouriadi, Ludovic Brucker, Mahdi Navari, Marie Dumont, Richard Kelly, Rhae Sung Kim, Tien-Hao Liao, Firoz Borah, and Xiaolan Xu
The Cryosphere, 16, 3531–3573, https://doi.org/10.5194/tc-16-3531-2022, https://doi.org/10.5194/tc-16-3531-2022, 2022
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Snow water equivalent (SWE) is of fundamental importance to water, energy, and geochemical cycles but is poorly observed globally. Synthetic aperture radar (SAR) measurements at X- and Ku-band can address this gap. This review serves to inform the broad snow research, monitoring, and application communities about the progress made in recent decades to move towards a new satellite mission capable of addressing the needs of the geoscience researchers and users.
G. Li, X. Gao, F. Hu, A. Guo, Z. Liu, J. Chen, C. Liu, S. Nie, and A. Fu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 53–58, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-53-2022, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-53-2022, 2022
Y. Tao, W. Huang, W. Gan, and H. Shen
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 209–215, https://doi.org/10.5194/isprs-annals-V-3-2022-209-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-209-2022, 2022
Shu Fang, Kebiao Mao, Xueqi Xia, Ping Wang, Jiancheng Shi, Sayed M. Bateni, Tongren Xu, Mengmeng Cao, Essam Heggy, and Zhihao Qin
Earth Syst. Sci. Data, 14, 1413–1432, https://doi.org/10.5194/essd-14-1413-2022, https://doi.org/10.5194/essd-14-1413-2022, 2022
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Air temperature is an important parameter reflecting climate change, and the current method of obtaining daily temperature is affected by many factors. In this study, we constructed a temperature model based on weather conditions and established a correction equation. The dataset of daily air temperature (Tmax, Tmin, and Tavg) in China from 1979 to 2018 was obtained with a spatial resolution of 0.1°. Accuracy verification shows that the dataset has reliable accuracy and high spatial resolution.
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Short summary
This study proposes a global-to-local approach for estimating forest height by fusing repeat-pass synthetic aperture radar interferometry and Global Ecosystem Dynamics Investigation (GEDI) data. Using Advanced Land Observing Satellite (ALOS-1) data and a twofold strategy to address temporal gaps, the method produced 30 m gridded forest height mosaics for the northeastern United States and China, demonstrating promising accuracies and offering potential for fusing data from future missions.
This study proposes a global-to-local approach for estimating forest height by fusing...
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