Articles | Volume 16, issue 7
https://doi.org/10.5194/essd-16-3213-2024
© 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-16-3213-2024
© 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
| 
10 Jul 2024
Data description paper |
| 10 Jul 2024
| 10 Jul 2024
ChinaSoyArea10m: a dataset of soybean-planting areas with a spatial resolution of 10 m across China from 2017 to 2021
Qinghang Mei
Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, Beijing Normal University, Zhuhai 519087, China
School of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519087, China
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Zhao Zhang
CORRESPONDING AUTHOR
Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, Beijing Normal University, Zhuhai 519087, China
School of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519087, China
Jichong Han
Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, Beijing Normal University, Zhuhai 519087, China
School of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519087, China
School of Systems Science, Beijing Normal University, Beijing 100875, China
Jie Song
Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, Beijing Normal University, Zhuhai 519087, China
School of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519087, China
School of Systems Science, Beijing Normal University, Beijing 100875, China
Jinwei Dong
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
Huaqing Wu
Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, Beijing Normal University, Zhuhai 519087, China
School of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519087, China
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, Beijing Normal University, Zhuhai 519087, China
School of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519087, 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
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Cited
13 citations as recorded by crossref.
- Optimized Phosphorus Application Under Water Stress Enhances Photosynthesis, Physiological Traits, and Yield in Soybean During Flowering Stage Q. Chen et al. 10.3390/agronomy15020444
- Uncovering the spatiotemporal evolution and driving mechanisms of soybean planting area in China from 2000 to 2022 W. Liu et al. 10.1016/j.jia.2025.07.021
- Occurrence of per- and polyfluoroalkyl substances in wheat, maize, rice, and soybean from chinese major grain producing regions X. Li et al. 10.1016/j.jhazmat.2024.136509
- Remote sensing for crop mapping: A perspective on current and future crop-specific land cover data products C. Zhang et al. 10.1016/j.rse.2025.114995
- Major grain crop mapping in Northeast China using sample generation method and ensemble learning X. Hu et al. 10.1016/j.eja.2025.127678
- Global-PCG-10: a 10 m global map of plastic-covered greenhouses derived from Sentinel-2 in 2020 B. Niu et al. 10.5194/essd-17-5065-2025
- Vegetable Fields Mapping in Northeast China Based on Phenological Features J. Hu et al. 10.3390/agronomy15020307
- TWDTW-Based Maize Mapping Using Optimal Time Series Features of Sentinel-1 and Sentinel-2 Images H. Yan et al. 10.3390/rs17173113
- Monitoring of Cropland Abandonment Integrating Machine Learning and Google Earth Engine—Taking Hengyang City as an Example Y. Jiang & Z. Guo 10.3390/land14101984
- Estimating wastewater emissions and environmental levels of typical organic contaminants based on regionalized modelling R. Qin et al. 10.1016/j.envres.2025.120965
- ChinaSoyArea10m: a dataset of soybean-planting areas with a spatial resolution of 10 m across China from 2017 to 2021 Q. Mei et al. 10.5194/essd-16-3213-2024
- Mapping 1-km soybean yield across China from 2001 to 2020 based on ensemble learning M. Zhang et al. 10.1038/s41597-025-04738-x
- Mapping the harvest area of a comprehensive set of crop types in China from 1990 to 2020 at a 1-km resolution K. Dai et al. 10.1038/s41597-025-05723-0
10 citations as recorded by crossref.
- Optimized Phosphorus Application Under Water Stress Enhances Photosynthesis, Physiological Traits, and Yield in Soybean During Flowering Stage Q. Chen et al. 10.3390/agronomy15020444
- Uncovering the spatiotemporal evolution and driving mechanisms of soybean planting area in China from 2000 to 2022 W. Liu et al. 10.1016/j.jia.2025.07.021
- Occurrence of per- and polyfluoroalkyl substances in wheat, maize, rice, and soybean from chinese major grain producing regions X. Li et al. 10.1016/j.jhazmat.2024.136509
- Remote sensing for crop mapping: A perspective on current and future crop-specific land cover data products C. Zhang et al. 10.1016/j.rse.2025.114995
- Major grain crop mapping in Northeast China using sample generation method and ensemble learning X. Hu et al. 10.1016/j.eja.2025.127678
- Global-PCG-10: a 10 m global map of plastic-covered greenhouses derived from Sentinel-2 in 2020 B. Niu et al. 10.5194/essd-17-5065-2025
- Vegetable Fields Mapping in Northeast China Based on Phenological Features J. Hu et al. 10.3390/agronomy15020307
- TWDTW-Based Maize Mapping Using Optimal Time Series Features of Sentinel-1 and Sentinel-2 Images H. Yan et al. 10.3390/rs17173113
- Monitoring of Cropland Abandonment Integrating Machine Learning and Google Earth Engine—Taking Hengyang City as an Example Y. Jiang & Z. Guo 10.3390/land14101984
- Estimating wastewater emissions and environmental levels of typical organic contaminants based on regionalized modelling R. Qin et al. 10.1016/j.envres.2025.120965
3 citations as recorded by crossref.
- ChinaSoyArea10m: a dataset of soybean-planting areas with a spatial resolution of 10 m across China from 2017 to 2021 Q. Mei et al. 10.5194/essd-16-3213-2024
- Mapping 1-km soybean yield across China from 2001 to 2020 based on ensemble learning M. Zhang et al. 10.1038/s41597-025-04738-x
- Mapping the harvest area of a comprehensive set of crop types in China from 1990 to 2020 at a 1-km resolution K. Dai et al. 10.1038/s41597-025-05723-0
Latest update: 09 Oct 2025
Short summary
In order to make up for the lack of long-term soybean planting area maps in China, we firstly generated a dataset of soybean planting area with a spatial resolution of 10 m for major producing areas in China from 2017 to 2021 (ChinaSoyArea10m). Compared with existing datasets, ChinaSoyArea10m has higher consistency with census data and further improvement in spatial details. The dataset can provide reliable support for subsequent studies on yield monitoring and food security.
In order to make up for the lack of long-term soybean planting area maps in China, we firstly...
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