棉花学报2024，Vol.36Issue(1)：1-13,13.DOI:10.11963/cs20230026
基于无人机多光谱影像与机器学习算法的棉花冠层叶绿素含量估算研究
Estimation of chlorophyll content in cotton canopy using UAV multispectral imagery and machine learning algorithms
摘要
Abstract
[Objective]This study aims to monitor the chlorophyll content of cotton leaves by utilizing unmanned aerial vehicle(UAV)-based multispectral technology.[Methods]This study utilized multispectral images of cotton canopies obtained by UAV in southern Xinjiang and employed seven different machine learning methods to estimate the canopy chlorophyll content during the flowering and boll-setting stage which is the critical growth period of cotton.The seven methods include linear regression(LR)-based methods,i.e.,simple linear regression,partial least squares regression(PLSR),ridge regression(RR),least absolute shrinkage and selection operator(LASSO)regression,support vector regression(SVR),K-nearest neighbors regression(KNNR),and random forest regression(RFR).[Results]The results showed that compared with the LR method,the RFR,SVR and KNNR can improve the accuracy of prediction model of chlorophyll content in cotton canopies,especially the RFR algorithm,which had the coefficient of determination of 0.742,root mean square error of 1.158 mg L-1,residual predictive deviation of 1.969 with the validation dataset.[Conclusion]The use of UAV-based multispectral images with the RFR machine learning method,exhibits the most outstanding performance to estimate the chlorophyll content of cotton leaves and provide essential technical support for precision management in cotton field.关键词
无人机/多光谱/叶绿素含量/机器学习/遥感反演/棉花Key words
UAV/multispectral imagery/chlorophyll content/machine learning/remote sensing inversion/cotton引用本文复制引用
赵鑫,李朝阳,王洪博,刘江凡,江文格,赵泽艺,王兴鹏,高阳..基于无人机多光谱影像与机器学习算法的棉花冠层叶绿素含量估算研究[J].棉花学报,2024,36(1):1-13,13.基金项目
新疆生产建设兵团财政科技计划项目(2022BC009) （2022BC009）
现代农业工作重点实验室2022年度开放课题项目(TDNG2022103) （TDNG2022103）
中央级科研院所基本科研业务费专项(中国农业科学院农田灌溉研究所)资助项目(IFI2023-19) （中国农业科学院农田灌溉研究所）
国家重点研发计划(2022YFD1900505) （2022YFD1900505）
塔里木大学校级研创项目(TDGRI202253) （TDGRI202253）
