中国甜菜糖业Issue(4)：23-31,9.DOI:10.3969/j.issn.1002-0551.2023.04.005
无人机可见光影像对甜菜叶绿素含量的反演研究
Research on the Inversion of Chlorophyll Content of Sugar Beet by UAV Visible Light Image
摘要
Abstract
In order to study the correlation between UAV visible light vegetation index and chlorophyll content(chl)of sugar beet,real-time monitoring and management of sugar beet growth status,avoid traditional de-structive sampling,and guide precise application of nitrogen fertilizer.Based on the visible light remote sensing images of sugar beet under 9 different nitrogen application levels and the measured canopy chlorophyll content in the field,the growth of sugar beet was monitored by DJI Jingling 4 UAV,and the support vector machine(SVM),random forest(RF)and ridge regression(RR)machine learning models related to chlorophyll content were established.The accuracy of the model was evaluated by using the determination coefficient R2,root mean square error RMSE,normalized root mean square error NRMSE,mean absolute error MAE and other indicators.The results showed that in the sugar growth period of beet,the accuracy of chl inversion using SVM model was the best,with R2 of 0.74,RMSE of 0.68,MAE of 0.48 and NRMSE of 0.16.In the sugar accumulation period of sugar beet,only the SVM model met the requirements,R2 was 0.74,RMSE was 0.27,MAE was 0.18,and NRMSE was 0.16.In the whole growth period of sugar beet,the chl inversion accuracy of SVM model was still the highest,R2 was 0.76,RMSE was 0.53,MAE was 0.33,NRMSE was 0.09.Therefore,UAV remote sens-ing technology has important theoretical significance in the estimation of chlorophyll content in sugar beet,which can achieve accurate nitrogen application,yield increase,sugar increase and income increase.关键词
甜菜/无人机遥感/可见光/叶绿素/氮肥Key words
Beet/UAV Remote Sensing/Visible Light/Chlorophyll/Nitrogen Fertilizer分类
农业科技引用本文复制引用
刘智鑫,练雪萌,汪旭,吴啟贤,於丽华,耿贵..无人机可见光影像对甜菜叶绿素含量的反演研究[J].中国甜菜糖业,2023,(4):23-31,9.基金项目
国家糖料产业技术体系项目"甜菜种植制度"(CARS-170209) （CARS-170209）
