使用UAS衍生的多时空树冠特征进行棉花增长分析
Sindhu Palla1,2, Sayantan Sarkar2, Lei Zhao2,3
1Texas A&M University - Kingsville, Kingsville, TX, 78363, USA.
Scientific reports
|December 12, 2025
概括
空中无人机系统 (UAS) 提供了有价值的植物表型数据. 这项研究使用了UAS衍生的树冠高度来建模棉花的生长,评估成熟度和估计产量.
科学领域:
- 农业科学 农业科学
- 遥感 遥感 遥感 遥感
- 植物生理学 植物生理学
背景情况:
- 无人空中系统 (UAS) 在农业中越来越多地用于植物表型.
- 获取高分辨率的多时间数据对于理解作物生长动态至关重要.
研究的目的:
- 开发和验证一种分析来自UAS的棉花树冠高度数据的方法.
- 使用遥感数据将棉花生长参数与产量和成熟度相关联.
主要方法:
- 在2016年和2021年整个生长季节使用UAS收集RGB图像.
- 创建数字表面模型 (DSM) 来提取多时间的树冠高度 (CH) 测量.
- 将非线性增长函数,特别是五参数后勤函数,与CH数据相匹配,并分析其导数.
主要成果:
- 五个参数的物流函数准确地建模了棉花作物的生长 (R2=0.98,RMSE=6.41).
- 从模型中得出的最大增长率与棉花产量有很强的相关性 (R2=0.46在2016年,R2=0.68在2021年).
- 稳定生长阶段的开始准确地预测了棉花的基因型成熟度,准确率为80%.
结论:
- 基于UAS的遥感提供了一个强大的方法来监测棉花的生长和发展.
- 衍生生长度参数可以有效地用于产量估计和评估基因型成熟度.
- 这种方法支持明智的农业管理决策,包括植物生长调节剂的应用.
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