Inversion reflectance by apple tree canopy ground and unmanned aerial vehicle integrated remote sensing data
文献类型： 外文期刊
作者： Yu, Ruiyang 1 ; Zhu, Xicun 1 ; Bai, Xueyuan 1 ; Tian, Zhongyu 1 ; Jiang, Yuanmao 3 ; Yang, Guijun 4 ;
作者机构： 1.Shandong Agr Univ, Coll Resources & Environm, Tai An 271018, Shandong, Peoples R China
2.Shandong Agr Univ, Coll Resources, Natl Engn Lab Efficient Utilizat Soil & Fertilize, Tai An 271018, Shandong, Peoples R China
3.Shandong Agr Univ, Natl Apple Engn & Technol Res Ctr, Coll Hort Sci & Engn, Tai An 271018, Shandong, Peoples R China
4.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
关键词： Apple tree canopy; Integrated; Inversion; Reflectance; Remote sensing
期刊名称：JOURNAL OF PLANT RESEARCH （ 影响因子：2.629； 五年影响因子：2.926 ）
ISSN： 0918-9440
年卷期：
页码：
收录情况： SCI
摘要： To obtain accurate spatially continuous reflectance from Unmanned Aerial Vehicle (UAV) remote sensing, UAV data needs to be integrated with the data on the ground. Here, we tested accuracy of two methods to inverse reflectance, Ground-UAV-Linear Spectral Mixture Model (G-UAV-LSMM) and Minimum Noise Fraction-Pixel Purity Index-Linear Spectral Mixture Model (MNF-PPI-LSMM). At wavelengths of 550, 660, 735 and 790 nm, which were obtained by UAV multispectral observations, we calculated the canopy abundance based on the two methods to acquire the inversion reflectance. The correlation of the inversion and measured reflectance values was stronger in G-UAV-LSMM than MNF-PPI-LSMM. We conclude that G-UAV-LSMM is the better model to obtain the canopy inversion reflectance.
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