A 10 m maize, rice and soybean yield dataset from 2016 to 2021 in Northeast China

We generated a dataset of corn, rice, and soybean yields in Northeast China from 2016 to 2021, This dataset was developed by a method of yield calculated by APAR_(εg) from VPM model combined with transition coefficient. Validation results show that the model's mean relative errors (MRE) and relative root mean square errors (rRMSE) are 16.73% and 19.80% respectively for maize, 13.59% and 17.08% for rice, and 19.94% and 28.91% for soybean. The units of yield in this dataset are tons/hectare. The dataset offers valuable insights into crop yield distribution, supporting better agricultural decision–making and resource optimization.