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.

本数据集生成了2016至2021年中国东北地区玉米、水稻及大豆的产量数据。本数据集采用结合过渡系数的VPM模型（VPM model）中基于APAR_(εg)的产量计算方法构建而成。验证结果表明，该模型针对玉米的平均相对误差（mean relative errors, MRE）与相对均方根误差（relative root mean square errors, rRMSE）分别为16.73%和19.80%；针对水稻的两项指标分别为13.59%和17.08%；针对大豆则分别为19.94%和28.91%。本数据集的产量单位为吨/公顷。该数据集可为作物产量分布研究提供极具价值的参考依据，助力优化农业决策与资源配置。