基于无人驾驶飞行器的高光谱成像和机器学习是否在促进作物科学?
Alessandro Matese1, Joby M Prince Czarnecki2, Sathishkumar Samiappan2
1Geosystems Research Institute, Mississippi State University, Box 9627, Starkville, MS, USA; Institute of BioEconomy, National Research Council (CNR-IBE), Via Caproni 8, 50145 Florence, Italy.
Trends in plant science
|October 6, 2023
概括
基于无人机 (UAV) 的高光谱成像 (HSI) 和机器学习 (ML) 在农业中显示出希望. 然而,高成本和复杂性限制了许多作物的实际收益,需要更简单,更实惠的解决方案.
科学领域:
- 农业科学 农业科学
- 遥感 遥感 遥感 遥感
- 数据科学数据科学数据科学
背景情况:
- 在农业研究中对无人机 (UAV) 基础的高光谱成像 (HSI) 和机器学习 (ML) 的兴趣增加.
- 越来越多的关于这些主题的发表研究.
研究的目的:
- 为农业学家提供基于无人机的HSI和ML的最新评论.
- 与更简单的方法相比,强调使用无人机检索作物生物物理参数的好处.
主要方法:
- 评论了70多篇最近的研究论文.
- 基于无人机的HSI和ML在农业中的适用性和好处的分析.
主要成果:
- 在类似的研究中发现的一致结果很少.
- 目前基于无人机的HSI和ML方法的高复杂性和成本限制了实际效益,特别是对于低价值作物.
- 大多数经过审查的研究的好处很难为最终用户证明.
结论:
- 未来的研究应该专注于将发现简化为更低成本的选择.
- 为了更广泛的农业采用,需要开发更容易使用的基于无人机的HSI和ML工具.
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