Remote estimation of rice LAI based on Fourier spectrum texture from UAV image. - National Genomics Data Center (CNCB-NGDC)

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

Bo Duan, Yating Liu, Yan Gong, Yi Peng, Xianting Wu, Renshan Zhu, Shenghui Fang

Author Information

Bo Duan: 1School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China.
Yating Liu: 1School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China.
Yan Gong: 1School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China.
Yi Peng: 1School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China.
Xianting Wu: 2College of Life Sciences, Wuhan University, Wuhan, China.
Renshan Zhu: 2College of Life Sciences, Wuhan University, Wuhan, China.
Shenghui Fang: 1School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China.

PMID: 31695729 DOI: 10.1186/s13007-019-0507-8

BACKGROUND: The 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.
RESULTS: In 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.
CONCLUSIONS: In conclusion, the texture feature of high-resolution remote sensing images may be more effective in rice LAI estimation than the spectral feature.

Fourier spectrum texture Remote sensing Rice LAI UAV Vegetation index

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Front Plant Sci. 2019 Feb 27;10:204 [PMID: 30873194]
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Journal Article

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