Articles | Volume 17, issue 5
https://doi.org/10.5194/essd-17-2193-2025
https://doi.org/10.5194/essd-17-2193-2025
Data description paper
 | 
26 May 2025
Data description paper |  | 26 May 2025

CCD-Rice: a long-term paddy rice distribution dataset in China at 30 m resolution

Ruoque Shen, Qiongyan Peng, Xiangqian Li, Xiuzhi Chen, and Wenping Yuan

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CCD-Rice: A long-term paddy rice distribution dataset in China at 30 m resolution
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Cited articles

Belgiu, M. and Csillik, O.: Sentinel-2 cropland mapping using pixel-based and object-based time-weighted dynamic time warping analysis, Remote Sens. Environ., 204, 509–523, https://doi.org/10.1016/j.rse.2017.10.005, 2018. 
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Che, X., Zhang, H. K., Li, Z. B., Wang, Y., Sun, Q., Luo, D., and Wang, H.: Linearly interpolating missing values in time series helps little for land cover classification using recurrent or attention networks, ISPRS J. Photogramm., 212, 73–95, https://doi.org/10.1016/j.isprsjprs.2024.04.021, 2024. 
Che, Z., Purushotham, S., Cho, K., Sontag, D., and Liu, Y.: Recurrent Neural Networks for Multivariate Time Series with Missing Values, Sci. Rep., 8, 6085, https://doi.org/10.1038/s41598-018-24271-9, 2018. 
Clauss, K., Yan, H., and Kuenzer, C.: Mapping Paddy Rice in China in 2002, 2005, 2010 and 2014 with MODIS Time Series, Remote Sens., 8, 434, https://doi.org/10.3390/rs8050434, 2016. 
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Short summary
Rice is a vital staple crop that plays a crucial role in food security in China. However, long-term high-resolution rice distribution maps in China are lacking. This study developed a new rice-mapping method, mitigating the impact of cloud contamination and missing data in optical remote sensing observations on rice mapping. The resulting dataset, CCD-Rice (China Crop Dataset-Rice), achieved high accuracy and showed a strong correlation with statistical data.

 
 
 
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