Articles | Volume 13, issue 3
https://doi.org/10.5194/essd-13-1385-2021
© 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/essd-13-1385-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
31 Mar 2021
Data description paper |
| 31 Mar 2021
| 31 Mar 2021
Generating seamless global daily AMSR2 soil moisture (SGD-SM) long-term products for the years 2013–2019
Qiang Zhang
State Key Laboratory of Information Engineering, Survey Mapping and Remote Sensing, Wuhan University, Wuhan, China
School of Geodesy and Geomatics, Wuhan University, Wuhan, China
Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University, Wuhan, China
Jie Li
School of Geodesy and Geomatics, Wuhan University, Wuhan, China
Yuan Wang
School of Geodesy and Geomatics, Wuhan University, Wuhan, China
Fujun Sun
Beijing Electro-mechanical Engineering Institute, Beijing, China
Liangpei Zhang
CORRESPONDING AUTHOR
State Key Laboratory of Information Engineering, Survey Mapping and Remote Sensing, Wuhan University, Wuhan, China
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Short summary
Acquired daily soil moisture products are always incomplete globally (just about 30 %–80 % coverage ratio) due to the satellite orbit coverage and the limitations of soil moisture retrieval algorithms. To solve this inevitable problem, we generate long-term seamless global daily (SGD) AMSR2 soil moisture productions from 2013 to 2019. These productions are significant for full-coverage global daily hydrologic monitoring, rather than averaging as the monthly–quarter–yearly results.
Acquired daily soil moisture products are always incomplete globally (just about 30 %–80 %...
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