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

文献类型：期刊论文

作者Teng, Fei3,4; Wang, Minglei1,3; Shi, Wenjiao3,5; Pan, Li2; Guo, Jinghan3,5; Xiao, Xiangming2
刊名SCIENTIFIC DATA
出版日期2026-02-03
卷号13期号:1页码:344
DOI10.1038/s41597-026-06719-0
产权排序1
文献子类Article
英文摘要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 (APAR epsilon g\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\rm{APAR}}}_{{\varepsilon }_{g}}$$\end{document}) 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.
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WOS关键词GROSS PRIMARY PRODUCTION ; CARBON USE EFFICIENCY ; SATELLITE ; RESPIRATION ; INDEXES ; CROPS ; MODEL ; WHEAT
WOS研究方向Science & Technology - Other Topics
语种英语
WOS记录号WOS:001714592800006
出版者NATURE PORTFOLIO
源URL[http://ir.igsnrr.ac.cn/handle/311030/221351]  
专题陆地表层格局与模拟院重点实验室_外文论文
通讯作者Shi, Wenjiao
作者单位1.Shanxi Normal Univ, Collage Geog Sci, Taiyuan 030031, Peoples R China;
2.Univ Oklahoma, Sch Biol Sci, Norman, OK 73019 USA
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China;
4.Shanghai Surveying & Mapping Inst, Shanghai 200063, Peoples R China;
5.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China;
推荐引用方式
GB/T 7714		 Teng, Fei,Wang, Minglei,Shi, Wenjiao,et al. A 10 m maize, rice and soybean yield dataset from 2016 to 2021 in Northeast China[J]. SCIENTIFIC DATA,2026,13(1):344.
APA Teng, Fei,Wang, Minglei,Shi, Wenjiao,Pan, Li,Guo, Jinghan,&Xiao, Xiangming.(2026).A 10 m maize, rice and soybean yield dataset from 2016 to 2021 in Northeast China.SCIENTIFIC DATA,13(1),344.
MLA Teng, Fei,et al."A 10 m maize, rice and soybean yield dataset from 2016 to 2021 in Northeast China".SCIENTIFIC DATA 13.1(2026):344.

入库方式： OAI收割

来源：地理科学与资源研究所

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