Articles | Volume 15, issue 7
https://doi.org/10.5194/essd-15-3203-2023
© 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-15-3203-2023
© 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
| 
26 Jul 2023
Data description paper |
| 26 Jul 2023
| 26 Jul 2023
High-resolution distribution maps of single-season rice in China from 2017 to 2022
Ruoque Shen
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, Guangdong, China
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai 519082, Guangdong, China
Baihong Pan
Department of Microbiology and Plant Biology, University of Oklahoma,
Norman, OK 73019, USA
Qiongyan Peng
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, Guangdong, China
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai 519082, Guangdong, China
Jie Dong
College of Geomatics and Municipal Engineering, Zhejiang University
of Water Resources and Electric Power, Hangzhou 310018, Zhejiang, China
Xuebing Chen
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, Guangdong, China
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai 519082, Guangdong, China
Xi Zhang
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, Guangdong, China
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai 519082, Guangdong, China
Key Laboratory of Environmental Change and Natural Disaster, Ministry
of Education, Beijing Normal University, Beijing 100875, China
Jianxi Huang
College of Land Science and Technology, China Agricultural University,
Beijing 100083, China
Wenping Yuan
CORRESPONDING AUTHOR
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, Guangdong, China
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai 519082, Guangdong, China
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Cited
17 citations as recorded by crossref.
- Cotton lands induced cooling effect on land surface temperature in Xinjiang, China J. Dong et al. 10.1016/j.agrformet.2024.110004
- Tracking paddy rice acreage, flooding impacts, and mitigations during El Niño flooding events using Sentinel-1/2 imagery and cloud computing R. Liu et al. 10.1016/j.isprsjprs.2024.08.010
- 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
- A comprehensive review of rice mapping from satellite data: Algorithms, product characteristics and consistency assessment H. Fang et al. 10.1016/j.srs.2024.100172
- A novel and robust method for large-scale single-season rice mapping based on phenology and statistical data M. Yang et al. 10.1016/j.isprsjprs.2024.05.019
- A novel red-edge vegetable index for paddy rice mapping based on Sentinel-1/2 and GF-6 images Y. Wan et al. 10.1080/17538947.2024.2398068
- A High-Resolution Distribution Dataset of Paddy Rice in India Based on Satellite Data X. Chen et al. 10.3390/rs16173180
- Novel Harmonic-Based Scheme for Mapping Rice-Crop Intensity at a Large Scale Using Time-Series Sentinel-1 and ERA5-Land Datasets Z. He et al. 10.1109/TGRS.2024.3387559
- ChinaRiceCalendar – seasonal crop calendars for early-, middle-, and late-season rice in China H. Li et al. 10.5194/essd-16-1689-2024
- Mapping upland crop–rice cropping systems for targeted sustainable intensification in South China B. Qiu et al. 10.1016/j.cj.2023.12.010
- An automated sample generation method by integrating phenology domain optical-SAR features in rice cropping pattern mapping J. Yang et al. 10.1016/j.rse.2024.114387
- Comparison of Cloud-Mask Algorithms and Machine-Learning Methods Using Sentinel-2 Imagery for Mapping Paddy Rice in Jianghan Plain X. Gao et al. 10.3390/rs16071305
- Study on Spatiotemporal Characteristics and Influencing Factors of High-Resolution Single-Season Rice Y. Han et al. 10.3390/agronomy14102436
- Regional uncertainty analysis between crop phenology model structures and optimal parameters C. Yang et al. 10.1016/j.agrformet.2024.110137
- Identifying spatial and temporal dynamics and driving factors of cultivated land fragmentation in Shaanxi province Y. Zhao & Q. Feng 10.1016/j.agsy.2024.103948
- Single-Season Rice Area Mapping by Combining Multi-Temporal Polarization Decomposition Components and the Two-Stage Segmentation Method J. Jiang et al. 10.3390/agriculture14010002
- High-resolution distribution maps of single-season rice in China from 2017 to 2022 R. Shen et al. 10.5194/essd-15-3203-2023
15 citations as recorded by crossref.
- Cotton lands induced cooling effect on land surface temperature in Xinjiang, China J. Dong et al. 10.1016/j.agrformet.2024.110004
- Tracking paddy rice acreage, flooding impacts, and mitigations during El Niño flooding events using Sentinel-1/2 imagery and cloud computing R. Liu et al. 10.1016/j.isprsjprs.2024.08.010
- 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
- A comprehensive review of rice mapping from satellite data: Algorithms, product characteristics and consistency assessment H. Fang et al. 10.1016/j.srs.2024.100172
- A novel and robust method for large-scale single-season rice mapping based on phenology and statistical data M. Yang et al. 10.1016/j.isprsjprs.2024.05.019
- A novel red-edge vegetable index for paddy rice mapping based on Sentinel-1/2 and GF-6 images Y. Wan et al. 10.1080/17538947.2024.2398068
- A High-Resolution Distribution Dataset of Paddy Rice in India Based on Satellite Data X. Chen et al. 10.3390/rs16173180
- Novel Harmonic-Based Scheme for Mapping Rice-Crop Intensity at a Large Scale Using Time-Series Sentinel-1 and ERA5-Land Datasets Z. He et al. 10.1109/TGRS.2024.3387559
- ChinaRiceCalendar – seasonal crop calendars for early-, middle-, and late-season rice in China H. Li et al. 10.5194/essd-16-1689-2024
- Mapping upland crop–rice cropping systems for targeted sustainable intensification in South China B. Qiu et al. 10.1016/j.cj.2023.12.010
- An automated sample generation method by integrating phenology domain optical-SAR features in rice cropping pattern mapping J. Yang et al. 10.1016/j.rse.2024.114387
- Comparison of Cloud-Mask Algorithms and Machine-Learning Methods Using Sentinel-2 Imagery for Mapping Paddy Rice in Jianghan Plain X. Gao et al. 10.3390/rs16071305
- Study on Spatiotemporal Characteristics and Influencing Factors of High-Resolution Single-Season Rice Y. Han et al. 10.3390/agronomy14102436
- Regional uncertainty analysis between crop phenology model structures and optimal parameters C. Yang et al. 10.1016/j.agrformet.2024.110137
- Identifying spatial and temporal dynamics and driving factors of cultivated land fragmentation in Shaanxi province Y. Zhao & Q. Feng 10.1016/j.agsy.2024.103948
2 citations as recorded by crossref.
- Single-Season Rice Area Mapping by Combining Multi-Temporal Polarization Decomposition Components and the Two-Stage Segmentation Method J. Jiang et al. 10.3390/agriculture14010002
- High-resolution distribution maps of single-season rice in China from 2017 to 2022 R. Shen et al. 10.5194/essd-15-3203-2023
Latest update: 20 Nov 2024
Short summary
Paddy rice is the second-largest grain crop in China and plays an important role in ensuring global food security. This study developed a new rice-mapping method and produced distribution maps of single-season rice in 21 provincial administrative regions of China from 2017 to 2022 at a 10 or 20 m resolution. The accuracy was examined using 108 195 survey samples and county-level statistical data, and we found that the distribution maps have good accuracy.
Paddy rice is the second-largest grain crop in China and plays an important role in ensuring...
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