Articles | Volume 15, issue 1
https://doi.org/10.5194/essd-15-395-2023
© Author(s) 2023. 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-15-395-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
23 Jan 2023
Data description paper |
| 23 Jan 2023
| 23 Jan 2023
ChinaCropSM1 km: a fine 1 km daily soil moisture dataset for dryland wheat and maize across China during 1993–2018
Fei Cheng
Academy of Disaster Reduction and Emergency Management, Beijing Normal University, 100875 Beijing, China
Zhao Zhang
CORRESPONDING AUTHOR
Academy of Disaster Reduction and Emergency Management, Beijing Normal University, 100875 Beijing, China
School of National Safety and Emergency Management, Beijing Normal University, 100875 Beijing, China
Huimin Zhuang
Academy of Disaster Reduction and Emergency Management, Beijing Normal University, 100875 Beijing, China
Jichong Han
Academy of Disaster Reduction and Emergency Management, Beijing Normal University, 100875 Beijing, China
Yuchuan Luo
Academy of Disaster Reduction and Emergency Management, Beijing Normal University, 100875 Beijing, China
Juan Cao
Academy of Disaster Reduction and Emergency Management, Beijing Normal University, 100875 Beijing, China
Liangliang Zhang
Academy of Disaster Reduction and Emergency Management, Beijing Normal University, 100875 Beijing, China
Jing Zhang
Academy of Disaster Reduction and Emergency Management, Beijing Normal University, 100875 Beijing, China
Jialu Xu
School of National Safety and Emergency Management, Beijing Normal University, 100875 Beijing, China
Fulu Tao
Key Laboratory of Land Surface Pattern and Simulation, Institute of
Geographical Sciences and Natural Resources Research, Chinese Academy of
Sciences, Beijing 100101, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Climate Impacts Group, Natural Resources Institute Finland (Luke), 00790 Helsinki, Finland
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Short summary
We generated a 1 km daily soil moisture dataset for dryland wheat and maize across China (ChinaCropSM1 km) over 1993–2018 through random forest regression, based on in situ observations. Our improved products have a remarkably better quality compared with the public global products in terms of both spatial and time dimensions by integrating an irrigation module (crop type, phenology, soil depth). The dataset may be useful for agriculture drought monitoring and crop yield forecasting studies.
We generated a 1 km daily soil moisture dataset for dryland wheat and maize across China...
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