Remote estimation of rice LAI based on Fourier spectrum texture from UAV image

被引:74
|
作者
Duan, Bo [1 ]
Liu, Yating [1 ]
Gong, Yan [1 ,3 ]
Peng, Yi [1 ,3 ]
Wu, Xianting [2 ,3 ]
Zhu, Renshan [2 ,3 ]
Fang, Shenghui [1 ,3 ]
机构
[1] Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan, Hubei, Peoples R China
[2] Wuhan Univ, Coll Life Sci, Wuhan, Hubei, Peoples R China
[3] Wuhan Univ, Lab Remote Sensing Crop Phenotyping, Wuhan, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
Remote sensing; UAV; Rice LAI; Vegetation index; Fourier spectrum texture; HYPERSPECTRAL VEGETATION INDEXES; LEAF-AREA INDEX; CHLOROPHYLL CONTENT; NEURAL-NETWORK; WHEAT CROPS; REFLECTANCE; MODEL; ALGORITHMS; BIOMASS; YIELD;
D O I
10.1186/s13007-019-0507-8
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
BackgroundThe accurate estimation of rice LAI is particularly important to monitor rice growth status. Remote sensing, as a non-destructive measurement technology, has been proved to be useful for estimating vegetation growth parameters, especially at large scale. With the development of unmanned aerial vehicles (UAVs), this novel remote sensing platform has been widely used to provide remote sensing images which have much higher spatial resolution. Previous reports have shown that the spectral feature of remote sensing images could be an effective indicator to estimate vegetation growth parameters. However, the texture feature of high-resolution remote sensing images is rarely employed for this purpose. Besides, the physical mechanism between the texture feature and vegetation growth parameters is still unclear.ResultsIn this study, a Fourier spectrum texture based on the UAV Image was developed to estimate rice LAI. And the relationship between Fourier spectrum texture and rice LAI was also analyzed. The results showed that Fourier spectrum texture could improve the accuracy of rice LAI estimation.ConclusionsIn conclusion, the texture feature of high-resolution remote sensing images may be more effective in rice LAI estimation than the spectral feature.
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页数:12
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