Abstract
As one of the most widely cultivated grain crops, paddy rice is a vital staple food in China and plays a crucial role in ensuring food security. Over the past decades, the planting area of paddy rice in China has shown substantial variability. Yet, there are no long-term high-resolution rice distribution maps in China, which hinders our ability to estimate greenhouse gas fluxes and crop production. This study developed a new optical satellite-based rice-mapping method using a machine learning model and appropriate data preprocessing strategies to mitigate the impact of cloud contamination and missing data in optical remote sensing observations on rice mapping. This study produced CCD-Rice (China Crop Dataset-Rice), the first high-resolution rice distribution dataset in China from 1990 to 2016. Based on 394 753 validation samples, the overall accuracy of the distribution maps in each provincial administrative region averaged 89.61 %. Compared with 20 544 county-level statistical data, the coefficients of determination (R2) of single- and double-season rice in each year averaged 0.85 and 0.78, respectively. The distribution maps can be obtained at https://doi.org/10.57760/sciencedb.15865 (Shen et al., 2024a).
Cite
CITATION STYLE
Shen, R., Peng, Q., Li, X., Chen, X., & Yuan, W. (2025). CCD-Rice: a long-term paddy rice distribution dataset in China at 30 m resolution. Earth System Science Data, 17(5), 2193–2216. https://doi.org/10.5194/essd-17-2193-2025
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.