Hyperspectral Estimation of Nitrogen Content in Winter Wheat Leaves Based on Unmanned Aerial Vehicles

被引：0
|
作者：
Liu Mingxing [1 ,2 ,3 ,4 ]
Li Changchun [1 ]
Feng Haikuan [2 ,3 ,4 ]
Pei Haojie [1 ,2 ,3 ,4 ]
Li Zhenhai [2 ,3 ,4 ]
Yang Fuqin [5 ]
Yang Guijun [2 ,3 ,4 ]
Xu Shouzhi [6 ]
机构：
[1] Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo 454000, Henan, Peoples R China
[2] Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
[3] Minist Agr, Key Lab Informat Technol Agr, Beijing 100097, Peoples R China
[4] Beijing Engn Res Ctr Agr Internet Things, Beijing 100097, Peoples R China
[5] Henan Inst Engn, Coll Civil Engn, Zhengzhou 451191, Peoples R China
[6] Natl Calibrat Ctr Surveying Instruments, Beijing 100039, Peoples R China
来源：
COMPUTER AND COMPUTING TECHNOLOGIES IN AGRICULTURE XI, CCTA 2017, PT II | 2019年 / 546卷
基金：
中国国家自然科学基金;
关键词：
Unmanned aerial vehicles; Hyperspectral; Winter wheat; Leaf nitrogen content; Partial least squares method; REFLECTANCE;
D O I：
10.1007/978-3-030-06179-1_33
中图分类号：
S2 [农业工程];
学科分类号：
0828 ;
摘要：
Leaf nitrogen content is an important index of crop growth and plays an important role in crop growth and development. In this paper, the hyperspectral data of winter wheat and the leaf nitrogen content is used to study winter wheat on flagging stage, flowering stage and grain filling stage. The estimation model of nitrogen content in winter wheat leaves at different growth stages is constructed by using partial least squares method and verified by using a cross-validation method. The results showed that R2 and the RMSE of the three growth stages were 0.53, 0.68, 0.64 and 0.331%, 0.246% and 0.406% respectively, and R2 and RMSE of model validation were 0.44, 0.71, 0.64 and 0.369%, 0.235% and 0.410%. Both the prediction model and the verification model had high reliability. Therefore, it is feasible for UAV to carry hyperspectral monitoring system for retrieving nitrogen content of winter wheat leaves.
引用
收藏
页码：321 / 339
页数：19
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