Articles | Volume 16, issue 7
https://doi.org/10.5194/essd-16-3307-2024
© Author(s) 2024. 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-16-3307-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
19 Jul 2024
Data description paper |
| 19 Jul 2024
| 19 Jul 2024
A 10 m resolution land cover map of the Tibetan Plateau with detailed vegetation types
Xingyi Huang
Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Yuwei Yin
Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Luwei Feng
Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Xiaoye Tong
Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
Xiaoxin Zhang
Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
Jiangrong Li
Institute of Tibet Plateau Ecology, Tibet Agricultural and Animal Husbandry University, Linzhi, China
Feng Tian
CORRESPONDING AUTHOR
Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Perception and Effectiveness Assessment for Carbon-Neutrality Efforts, Engineering Research Center of Ministry of Education, Wuhan, China
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Hui Liang, Shunlin Liang, Bo Jiang, Tao He, Feng Tian, Jianglei Xu, Wenyuan Li, Fengjiao Zhang, and Husheng Fang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-136, https://doi.org/10.5194/essd-2025-136, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
This paper describes 1 km daily mean land surface sensible heat flux (H) and land surface – air temperature difference (Tsa) datasets on the global scale during 2000–2020. The datasets were developed using a data-driven approach and rigorously validated against in situ observations and existing H and Tsa datasets, demonstrating both high accuracy and exceptional spatial resolution.
Yufang Zhang, Shunlin Liang, Han Ma, Tao He, Feng Tian, Guodong Zhang, and Jianglei Xu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-553, https://doi.org/10.5194/essd-2024-553, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
Soil moisture (SM) plays a vital role in climate, agriculture, and hydrology, yet reliable long-term seamless global datasets remain scarce. To fill this gap, we developed a four-decade seamless global daily 5 km SM product using multi-source datasets and deep learning techniques. This product has long-term coverage, spatial and temporal integrity, and high accuracy, making it a valuable tool for applications like SM trend analysis, drought monitoring, and assessing vegetation responses.
M. C. A. Picoli, J. Radoux, X. Tong, A. Bey, P. Rufin, M. Brandt, R. Fensholt, and P. Meyfroidt
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 975–981, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-975-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-975-2022, 2022
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Short summary
The Tibetan Plateau, with its diverse vegetation ranging from forests to alpine grasslands, plays a key role in understanding climate change impacts. Existing maps lack detail or miss unique ecosystems. Our research, using advanced satellite technology and machine learning, produced the map TP_LC10-2022. Comparisons with other maps revealed TP_LC10-2022's excellence in capturing local variations. Our map is significant for in-depth ecological studies.
The Tibetan Plateau, with its diverse vegetation ranging from forests to alpine grasslands,...
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