Articles | Volume 15, issue 4
https://doi.org/10.5194/essd-15-1501-2023
© 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-15-1501-2023
© 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
| 
04 Apr 2023
Data description paper |
| 04 Apr 2023
| 04 Apr 2023
Twenty-meter annual paddy rice area map for mainland Southeast Asia using Sentinel-1 synthetic-aperture-radar data
Chunling Sun
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100094, China
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
College of Resources and Environment, University of Chinese Academy of
Sciences, Beijing 100049, China
Hong Zhang
CORRESPONDING AUTHOR
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100094, China
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
College of Resources and Environment, University of Chinese Academy of
Sciences, Beijing 100049, China
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100094, China
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
Ji Ge
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100094, China
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
College of Resources and Environment, University of Chinese Academy of
Sciences, Beijing 100049, China
Jingling Jiang
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100094, China
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
College of Resources and Environment, University of Chinese Academy of
Sciences, Beijing 100049, China
Lijun Zuo
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100094, China
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
Chao Wang
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100094, China
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
College of Resources and Environment, University of Chinese Academy of
Sciences, Beijing 100049, China
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Hong Zhang, Mingyang Song, Yinhaibin Ding, Yazhe Xie, Huadong Guo, Lu Xu, Ji Ge, Yafei Zhu, Shenghan Wang, Zihuan Guo, Zhe Wang, Haoxuan Duan, Lijun Zuo, and Wenjiang Huang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-24, https://doi.org/10.5194/essd-2026-24, 2026
Preprint under review for ESSD
Short summary
Short summary
Accurate rice farming data is vital for global food security. We created GlobalRice20, a global map of paddy rice at 20-meter resolution for 2015 and 2024. By utilizing satellite imagery and advanced processing to overcome cloud issues, this dataset fills a critical gap in agricultural monitoring. It provides a reliable baseline for analyzing food production trends and helps policymakers track progress toward the Sustainable Development Goal of Zero Hunger.
Jingling Jiang, Hong Zhang, Ji Ge, Lijun Zuo, Lu Xu, Mingyang Song, Yinhaibin Ding, Yazhe Xie, and Wenjiang Huang
Earth Syst. Sci. Data, 17, 1781–1805, https://doi.org/10.5194/essd-17-1781-2025, https://doi.org/10.5194/essd-17-1781-2025, 2025
Short summary
Short summary
This study uses temporal synthetic aperture radar (SAR) data and optical imagery to conduct rice-mapping experiments in 34 African countries with rice-planting areas exceeding 5000 ha in 2022, achieving a 20 m resolution spatial distribution mapping for 2023. The average classification accuracy based on the validation set exceeded 85 %, and the R2; values for linear fitting with existing statistical data all surpassed 0.9, demonstrating the effectiveness of the proposed mapping method.
Mingyang Song, Lu Xu, Ji Ge, Hong Zhang, Lijun Zuo, Jingling Jiang, Yinhaibin Ding, Yazhe Xie, and Fan Wu
Earth Syst. Sci. Data, 17, 661–683, https://doi.org/10.5194/essd-17-661-2025, https://doi.org/10.5194/essd-17-661-2025, 2025
Short summary
Short summary
We created a 10 m resolution rice distribution map for East Asia in 2023 (EARice10), achieving an overall accuracy (OA) of 90.48 % on validation samples. EARice10 shows strong consistency with statistical data (coefficient of determination, R2: 0.94–0.98) and existing datasets (R2: 0.79–0.98). It is the most up-to-date map, covering the four major rice-producing countries in East Asia at 10 m resolution.
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Short summary
Over 90 % of the world’s rice is produced in the Asia–Pacific region. In this study, a rice-mapping method based on Sentinel-1 data for mainland Southeast Asia is proposed. A combination of spatiotemporal features with strong generalization is selected and input into the U-Net model to obtain a 20 m resolution rice area map of mainland Southeast Asia in 2019. The accuracy of the proposed method is 92.20 %. The rice area map is concordant with statistics and other rice area maps.
Over 90 % of the world’s rice is produced in the Asia–Pacific region. In this study, a...
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