建立一个知识结构,用于用无人驾驶飞行器预测谷物作物的产量
Ghulam Mustafa1,2, Yuhong Liu1, Imran Haider Khan2
1Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, College of Environment, Hohai University, Nanjing, China.
Frontiers in plant science
|August 26, 2024
概括
无人驾驶飞行器 (UAV) 显著提升了谷物作物产量预测 (YP). 这项研究绘制了研究格局,确定了小麦,玉米,大米和大豆的关键贡献者和未来方向.
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:
- 无人驾驶飞行器 (UAV) 的快速发展刺激了农业产量预测 (YP) 的重大研究.
- 对于主要谷物作物的UAV-based YP,现有的文献需要全面分析,以了解其结构并识别新兴趋势.
研究的目的:
- 想象基于无人机的小麦,玉米,大米和大豆 (WMRS) 的YP的知识背景,研究进展和知识结构.
- 确定主要的研究前沿,重要贡献者 (国家,机构,作者,期刊) 和在无人机驱动的YP中的合作模式.
- 在微,中和宏层面分析YP贡献,包括数据类型,算法和研究地点.
主要方法:
- 从Web of Science核心收藏 (WOSCC) 获取2001年1月至2023年8月期间发表的研究文章的综合文献综述.
- 使用VOSviewer软件创建无人机相关知识的可视化网络,用于WMRS作物产量预测.
- 对贡献的国家,机构,作者,期刊,关键词,赠款和合作国家的分析.
主要成果:
- 确定了主要活跃的国家,多产出版物,富有成效的作者,顶级机构和在基于UAV的YP研究中具有影响力的期刊.
- 揭示了中国,美国,德国和澳大利亚的政策援助,显著提升了无人机连接的YP知识.
- 详细的数据类型,算法,结果和研究地点的详细发现,用于使用无人机预测WMRS作物产量.
结论:
- 该研究提供了一个清晰的可视化基于无人机的YP研究景观的主要谷物作物.
- 它突出了关键的子领域,并建议在遥感社区进行未来研究的新研究前沿.
- 了解这些动态有助于将努力集中在以后无人机驱动的农业研究的重要方向上.
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