NESEA-Rice10: high-resolution annual paddy rice maps for Northeast and Southeast Asia from 2017 to 2019

[摘要] An accurate paddy rice map is crucial for ensuring foodsecurity, particularly for Southeast and Northeast Asia. MODIS satellitedata are useful for mapping paddy rice at continental scales but have amixed-pixel problem caused by the coarse spatial resolution. To reduce themixed pixels, we designed a rule-based method for mapping paddy rice byintegrating time series Sentinel-1 and MODIS data. We demonstrated themethod by generating annual paddy rice maps for Southeast and Northeast Asia in 2017–2019 (NESEA-Rice10). We compared the resultant paddy rice maps withavailable agricultural statistics at subnational levels and existing ricemaps for some countries. The results demonstrated that the linearcoefficient of determination ( R 2 ) between our paddy rice maps andagricultural statistics ranged from 0.80 to 0.97. The paddy rice plantingareas in 2017 were spatially consistent with the existing maps in Vietnam( R 2 =0.93 ) and Northeast China ( R 2 =0.99 ). The spatialdistribution of the 2017–2019 composite paddy rice map was consistent withthat of the rice map from the International Rice Research Institute. Thepaddy rice planting area may have been underestimated in the region in whichthe flooding signal was not strong. The dataset is useful for water resource management, rice growth, and yield monitoring. The full product is publicly available at https://doi.org/10.5281/zenodo.5645344 (Han et al., 2021a). Small examples can be found from the following DOI: https://doi.org/10.17632/cnc3tkbwcm.1 (Han et al., 2021b).

[学科分类] 眼科学