ESTIMATION OF LEAF AREA INDEX OF WINTER WHEAT BASED ON HYPERSPECTRAL DATA OF UNMANNED AERIAL VEHICLES
文献类型： 外文期刊
作者： Chen, Riqiang 1 ; Feng, Haikuan 2 ; Yang, Fuqin 5 ; Li, Changchun 1 ; Yang, Guijun 2 ; Pei, Haojie 1 ; Pan, Li 2 ; Chen, Peng 1 ;
作者机构： 1.Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo 454000, Henan, Peoples R China
2.Minist Agr, Key Lab Quantitat Remote Sensing Agr, Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
3.Natl Engn Res Ctr 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, Henan, Peoples R China
6.Liaoning Tech Univ, Sch Geomat, Fuxing 123000, Peoples R China
关键词： Winter wheat; UAV remote sensing; Hyperspectral images; Leaf area index; Optimal Index
期刊名称：2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019)
ISSN： 2153-6996
年卷期： 2019 年
页码：
收录情况： SCI
摘要： Rapid and accurate estimation of the winter wheat leaf area index (LAI) is important for evaluating its growth and estimating yield. In this paper, Optimal Index (0I) was used to screen the best combination of hyperspectral bands in the flag stage and flowering period of wheat, and the LAI estimation model was constructed by Partial Least Square (PLS). The main results are as follows: The LAI estimation model based on the 614-774-794nm band combination is the best model for winter wheat flag stage (R-2=0.485, RMSE=1.192, =0.682, RMSEv=1.210); The LAI estimation model constructed by the 454-754-834nm band combination is the best model for winter wheat flowering (R-2=0.702, RMSE=0.665, Mr= 0.810, RMSEv=0.468). The results show that it is feasible to use the optimal band combination as an independent variable to estimate the leaf area index of winter wheat, which can be used as a new method to monitor the growth of wheat.
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