2026-03-23 中国科学院（CAS）
＜関連情報＞
- https://english.cas.cn/newsroom/research-news/202603/t20260323_1153141.shtml
- https://www.nature.com/articles/s41597-026-06719-0
中国東北部における2016年から2021年までのトウモロコシ、米、大豆の収量データセット（10m解像度） A 10 m maize, rice and soybean yield dataset from 2016 to 2021 in Northeast China
Fei Teng,Minglei Wang,Wenjiao Shi,Li Pan,Jinghan Guo & Xiangming Xiao
Scientific Data Published:03 February 2026
DOI:https://doi.org/10.1038/s41597-026-06719-0
Abstract
Accurate mapping of crop yields is essential for informed agricultural decision-making and optimal allocation of resources. Current crop yield datasets are deficient in large-scale, high-resolution information regarding the long-term spatial and temporal distribution of crop yields. To address this challenge, we developed a method of vegetation photosynthesis model combined with transition coefficient, producing a detailed dataset with 10 m resolution, covering major regions of maize, rice, and soybean in Northeast China from 2016 to 2021. The method introduces a dynamic observation index (APARεg) and a composite yield-conversion coefficient (a), which presents an innovative method for estimating crop yields without field measurements. Validation results show that, for maize, rice, and soybean, the model achieves r values of 0.39, 0.51, and 0.52; MREs of 12.14%, 11.96%, and 14.06%; and rRMSEs of 16.97%, 16.12%, and 17.26%, respectively. The dataset offers valuable insights into crop yield distribution, supporting better agricultural decision-making and resource optimization.
