华南农业大学学报2024，Vol.45Issue(4)：608-617,10.DOI:10.7671/j.issn.1001-411X.202310025
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
摘要
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分类
农业科技引用本文复制引用
陈盛德,陈一钢,徐小杰,刘俊宇,郭健洲,胡诗云,兰玉彬..基于无人机多光谱遥感的玉米LAI监测研究[J].华南农业大学学报,2024,45(4):608-617,10.基金项目
广东省自然科学基金(2022A1515011535) （2022A1515011535）
广州市科技计划(202201010642) （202201010642）
岭南现代农业科学与技术广东省实验室项目(NT2021009) （NT2021009）
