中国农业科技导报2024，Vol.26Issue(3)：91-97,7.DOI:10.13304/j.nykjdb.2022.1066
基于无人机航拍的苎麻倒伏信息解译研究
Research on Interpretation of Ramie Lodging Information Based on Unmanned Aerial Vehicles
摘要
Abstract
The most common damage to ramie tramet cultivation is stem loading.Traditional monitoring methods have drawbacks such as being time-consuming and inefficient.A method for obtaining ramie lodging information was investigated by unmanned aerial vehicles(UAV)in this study.Firstly,the canopy orthophoto and digital surface model(DSM)of ramie were created using Pix4D Mapper software.Then,the spectral,textural,and shape features of the canopy were extracted from the DSM,along with the canopy height index.Finally,a combination of 3 machine learning algorithms was used to createa classification model for normal and lodging canopies.The results showed that the DSM-based extracted plant height information could effectively replace the actual measured plant height in the field,with a model R2 of 0.899.The spectral,textural,shape,and height characteristics of fallen and normal ramets differed.The support vector machine and decision tree models outperformed the other learning algorithms,achieving 99％accuracy and efficiently identifying normal/lodging ramie plots.Above results provided technical assistance for accurate and rapid assessment of crop lodging.关键词
苎麻/倒伏/无人机/可见光相机/数字表面模型Key words
ramie/lodging/unmanned aerial vehicles(UAV)/visible light camera/digital surface model(DSM)分类
农业科技引用本文复制引用
王薇,付虹雨,卢建宁,岳云开,杨瑞芳,崔国贤,佘玮..基于无人机航拍的苎麻倒伏信息解译研究[J].中国农业科技导报,2024,26(3):91-97,7.基金项目
国家重点研发计划项目(2018YFD0201106) （2018YFD0201106）
国家现代农业产业技术体系建设项目(CARS-16-E11) （CARS-16-E11）
国家自然科学基金项目(31471543) （31471543）
湖南省教育厅重点项目(23A0178). （23A0178）
