Remote estimation of rice LAI based on Fourier spectrum texture from UAV image
Abstract 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 u...
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doaj-675c60124795481bae9bf1bed5cfa2c42020-11-25T04:02:09ZengBMCPlant Methods1746-48112019-11-0115111210.1186/s13007-019-0507-8Remote estimation of rice LAI based on Fourier spectrum texture from UAV imageBo Duan0Yating Liu1Yan Gong2Yi Peng3Xianting Wu4Renshan Zhu5Shenghui Fang6School of Remote Sensing and Information Engineering, Wuhan UniversitySchool of Remote Sensing and Information Engineering, Wuhan UniversitySchool of Remote Sensing and Information Engineering, Wuhan UniversitySchool of Remote Sensing and Information Engineering, Wuhan UniversityCollege of Life Sciences, Wuhan UniversityCollege of Life Sciences, Wuhan UniversitySchool of Remote Sensing and Information Engineering, Wuhan UniversityAbstract 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.http://link.springer.com/article/10.1186/s13007-019-0507-8Remote sensingUAVRice LAIVegetation indexFourier spectrum texture |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Bo Duan Yating Liu Yan Gong Yi Peng Xianting Wu Renshan Zhu Shenghui Fang |
spellingShingle |
Bo Duan Yating Liu Yan Gong Yi Peng Xianting Wu Renshan Zhu Shenghui Fang Remote estimation of rice LAI based on Fourier spectrum texture from UAV image Plant Methods Remote sensing UAV Rice LAI Vegetation index Fourier spectrum texture |
author_facet |
Bo Duan Yating Liu Yan Gong Yi Peng Xianting Wu Renshan Zhu Shenghui Fang |
author_sort |
Bo Duan |
title |
Remote estimation of rice LAI based on Fourier spectrum texture from UAV image |
title_short |
Remote estimation of rice LAI based on Fourier spectrum texture from UAV image |
title_full |
Remote estimation of rice LAI based on Fourier spectrum texture from UAV image |
title_fullStr |
Remote estimation of rice LAI based on Fourier spectrum texture from UAV image |
title_full_unstemmed |
Remote estimation of rice LAI based on Fourier spectrum texture from UAV image |
title_sort |
remote estimation of rice lai based on fourier spectrum texture from uav image |
publisher |
BMC |
series |
Plant Methods |
issn |
1746-4811 |
publishDate |
2019-11-01 |
description |
Abstract 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. |
topic |
Remote sensing UAV Rice LAI Vegetation index Fourier spectrum texture |
url |
http://link.springer.com/article/10.1186/s13007-019-0507-8 |
work_keys_str_mv |
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