基于无人机多光谱遥感的玉米LAI监测研究
Monitoring of corn leaf area index based on multispectral remote sensing of UAV
陈盛德 1陈一钢 2徐小杰 2刘俊宇 2郭健洲 2胡诗云 2兰玉彬1
作者信息
- 1. 华南农业大学电子工程学院(人工智能学院)/国家精准农业航空施药技术国际联合研究中心,广东广州 510642;岭南现代农业科学与技术广东省实验室,广东广州 510642
- 2. 华南农业大学电子工程学院(人工智能学院)/国家精准农业航空施药技术国际联合研究中心,广东广州 510642
- 折叠
摘要
[目的]探究更高效估测玉米LAI的无人机多光谱遥感监测模型,实现对玉米叶面积指数(Leaf area index,LAI)的快速预测估算.[方法]以全生长周期的玉米植株为研究对象,通过多光谱遥感无人机获取玉米植株影像并实地采集玉米LAI,利用多光谱信息研究植被指数与玉米LAI之间的定量关系,并选择相关的植被指数;分别使用多元线性逐步回归、支持向量机回归算法(Support vector machine regression,SVM)、随机森林回归算法(Random forest regression,RF)和基于鲸鱼算法(Whale optimization algorithm,WOA)优化的随机森林算法(WOA-RF)构建玉米LAI预测模型,通过分析对比,选择最优预测模型.[结果]筛选出的植被指数NDVI、NDRE、EVI、CIG与LAI呈极显著相关(P<0.01),构建了多元线性回归模型、SVM模型、RF模型和WOA-RF模型的预测模型,R2 分别为 0.873 2、0.878 0、0.917 7 和 0.940 8,RMSE分别为 0.277 5、0.236 5、0.209 0 和0.128 7.[结论]基于WOA-RF的玉米LAI预测模型的预测精度能够满足玉米生产的需要,对玉米生长期间的种植管理具有指导意义.
Abstract
[Objective]In order to achieve a rapid estimation of the leaf area index(LAI)of maize,this study explores a more efficient monitoring model for maize LAI estimation based multispectral remote sensing of unmanned aerial vehicle(UAV).[Method]This study focused on maize plants throughout their entire growth cycle.Multispectral imagery of maize plants was acquired using UAV,and maize LAI were collected in field.The quantitative relationship between vegetation index and maize LAI was investigated using multispectral information to select relevant vegetation indices.Multiple linear stepwise regression,support vector machine regression(SVM),random forest regression(RF),and a random forest algorithm optimized using whale optimization algorithm(WOA-RF)were used to construct maize LAI prediction models,respectively.The best prediction model was selected on the basis of comparison.[Result]The vegetation indices of NDVI,NDRE,EVI and CIG were highly correlated with LAI(P<0.01).The models of multiple linear regression,SVM,RF,and WOA-RF were constructed,with R-squared values of 0.873 2,0.878 0,0.917 7,and 0.940 8 respectively,and the root mean square error(RMSE)values of 0.277 5,0.236 5,0.209 0,and 0.128 7 respectively.[Conclusion]The prediction model of maize LAI based on WOA-RF provides a high level of accuracy,which can meet the requirement for maize production.It can be used to guide planting management of maize during the growth period.
关键词
无人机(UAV)/遥感/多光谱/玉米/叶面积指数(LAI)/监测Key words
Unmanned aerial vehicle(UAV)/Remote sensing/Multispectral/Corn/Leaf area index(LAI)/Monitoring引用本文复制引用
基金项目
广东省自然科学基金(2022A1515011535)
广州市科技计划(202201010642)
岭南现代农业科学与技术广东省实验室项目(NT2021009)
出版年
2024
国家科技期刊平台
NSTL
万方数据