从2001年到2020年,根据集体学习的基础,在中国绘制1公里的大豆产量
Min Zhang1, Xinlei Xu1, Junji Ou1
1College of Land Science and Technology, State Key Laboratory of Efficient Utilization of Agricultural Water Resources, China Agricultural University, Beijing, 100193, China.
Scientific data
|March 8, 2025
概括
中国面临着严重的大豆进口依赖. 一个新的高分辨率数据集,ChinaSoyYield1km,通过详细介绍2001-2020年大豆产量变化来帮助农业政策.
科学领域:
- 农业科学 农业科学
- 地理空间数据科学数据科学
- 环境科学 环境科学
背景情况:
- 由于国内生产不足,中国对大豆的大量需求需要进口.
- 优化国内种植结构和农业政策需要准确,高分辨率的产量数据.
研究的目的:
- 为中国 (2001-2020年) 开发一个高分辨率 (1公里) 的每年大豆产量数据集,命名为ChinaSoyYield1km.
- 为农业政策提供信息和优化大豆种植战略提供数据驱动工具.
主要方法:
- 利用集体学习算法和空间分解技术.
- 综合多源数据,包括气候变量,遥感图像,土壤特性,农业管理和官方产量记录.
- 为年度大豆产量数据集实现了1公里的空间分辨率.
主要成果:
- 中国SoyYield1km数据集捕捉了超过50%的县级收益率变化.
- 与现有数据集相比,证明了更高的准确性,根平均平方误差 (RMSE) 减少了0.180.60t/ha.
- 提供了对影响大豆产量的因素的细微了解.
结论:
- 中国SoyYield1km数据集是加强农业研究和政策制定的宝贵资源.
- 促进科学界和政府改善大豆种植的规划和决策.
- 通过基于数据的策略,为解决中国大豆供需不平衡做出贡献.
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