基于遥感的玉米生长过程参数揭示了玉米产量:田间和区域规模的比较
Minghan Cheng1,2,3,4, Xiuliang Jin5,6,7,8, Chenwei Nie3,4
1Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Key Laboratory of Crop Cultivation and Physiology, Agricultural College, Yangzhou University, Yangzhou, 225009, People's Republic of China.
BMC plant biology
|February 5, 2025
概括
准确的作物产量估计使用长期遥感数据来跟踪玉米的生长. 该方法使用叶面积指数 (LAI) 衍生参数,适用于田间和区域规模,改善农业管理.
科学领域:
- 农业科学 农业科学
- 遥感 遥感 遥感 遥感
- 农业学是一种农业学.
背景情况:
- 准确的区域作物产量估计对于农业资源分配和经济优化至关重要.
- 以前的产量估计方法往往缺乏全面的作物生长描述和跨度适用性.
- 长期遥感观测为评估作物生长状况提供了一个全面的方法.
研究的目的:
- 利用从叶面积指数 (LAI) 获得的生长过程参数开发玉米产量估计模型.
- 确保模型在不同的观测尺度 (无人机和卫星) 上适用.
- 确定影响收益率估计准确性的关键增长参数.
主要方法:
- 从无人机和卫星衍生的LAI数据中提取了四个玉米生长过程参数 (PP_a,PP_b,PP_c,LAImax).
- 使用这四个参数构建了玉米产量估计模型.
- 评估了模型的准确性和空间适用性,无论是在现场还是区域范围内.
主要成果:
- 开发的模型准确地估计了玉米产量,田间规模的rRMSE为14.08%,区域规模为17.75%.
- 增长时间 (PP_a) 和最大LAI是对收益率估计准确性的最重要的贡献因素.
- 该方法表现出良好的空间适用性,莫兰指数值为-0.18 (现场规模) 和0.19 (区域规模).
结论:
- 来自长期遥感的玉米生长过程参数有效地估计了跨尺度的产量.
- 这种方法支持优化农业实践 (UAV) 和区域农业政策决策 (卫星).
- 利用基于过程的参数进行产量估计为农业研究提供了一个新的视角.
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