Articles | Volume 15, issue 9
https://doi.org/10.5194/essd-15-4047-2023
© 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-15-4047-2023
© 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
| 
13 Sep 2023
Data description paper |
| 13 Sep 2023
| 13 Sep 2023
ChinaWheatYield30m: a 30 m annual winter wheat yield dataset from 2016 to 2021 in China
Yu Zhao
Key Laboratory of Quantitative Remote Sensing in Agriculture of
Ministry of Agriculture and Rural Affairs, Information Technology Research
Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing
100097, China
College of agriculture, Shanxi Agricultural University, Taigu, Shanxi
030801, China
Shaoyu Han
Key Laboratory of Quantitative Remote Sensing in Agriculture of
Ministry of Agriculture and Rural Affairs, Information Technology Research
Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing
100097, China
Institute of Agricultural Economics and Information, Henan Academy of
Agricultural Sciences, Zhengzhou, Henan 450000, China
Jie Zheng
Key Laboratory of Quantitative Remote Sensing in Agriculture of
Ministry of Agriculture and Rural Affairs, Information Technology Research
Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing
100097, China
Hanyu Xue
Key Laboratory of Quantitative Remote Sensing in Agriculture of
Ministry of Agriculture and Rural Affairs, Information Technology Research
Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing
100097, China
Zhenhai Li
Key Laboratory of Quantitative Remote Sensing in Agriculture of
Ministry of Agriculture and Rural Affairs, Information Technology Research
Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing
100097, China
College of Geodesy and Geomatics, Shandong University of Science and
Technology, Qingdao 266590, China
Yang Meng
Key Laboratory of Quantitative Remote Sensing in Agriculture of
Ministry of Agriculture and Rural Affairs, Information Technology Research
Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing
100097, China
College of agriculture, Shanxi Agricultural University, Taigu, Shanxi
030801, China
Xuguang Li
Cultivated Land Monitoring and Protection Center of Hebei,
Shijiazhuang, 050056, China
Xiaodong Yang
Key Laboratory of Quantitative Remote Sensing in Agriculture of
Ministry of Agriculture and Rural Affairs, Information Technology Research
Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing
100097, China
Zhenhong Li
School of Geological Engineering and Geomatics, Chang'an University,
Xi'an 710054, China
Shuhong Cai
Cultivated Land Monitoring and Protection Center of Hebei,
Shijiazhuang, 050056, China
Guijun Yang
CORRESPONDING AUTHOR
Key Laboratory of Quantitative Remote Sensing in Agriculture of
Ministry of Agriculture and Rural Affairs, Information Technology Research
Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing
100097, China
School of Geological Engineering and Geomatics, Chang'an University,
Xi'an 710054, China
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EGUsphere, https://doi.org/10.5194/egusphere-2026-142, https://doi.org/10.5194/egusphere-2026-142, 2026
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
From April to June 2024, the North China Plain experienced an extreme dry-hot event. Satellite data showed rapid crop growth in April but record-low levels in June under combined heat and drought stress. Consistent with vegetation signals, Yield statistics and field observations confirmed higher winter wheat yields but lower summer maize yields. Growth was enhanced by warming and carryover in April, dominated by carryover in May, and strongly limited by high vapor pressure deficit in June.
C. Zhao, Z. Li, S. Zhang, G. Huang, C. Yang, and S. Duan
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-5-W1-2023, 59–64, https://doi.org/10.5194/isprs-archives-XLVIII-5-W1-2023-59-2023, https://doi.org/10.5194/isprs-archives-XLVIII-5-W1-2023-59-2023, 2023
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Short summary
In the present study, we generated a 30 m Chinese winter wheat yield dataset from 2016 to 2021, called ChinaWheatYield30m. The dataset has high spatial resolution and great accuracy. It is the highest-resolution yield dataset known. Such a dataset will provide basic knowledge of detailed wheat yield distribution, which can be applied for many purposes including crop production modeling or regional climate evaluation.
In the present study, we generated a 30 m Chinese winter wheat yield dataset from 2016 to 2021,...
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