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Remote estimation of rice LAI based on Fourier spectrum texture from UAV image
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6824110/ https://www.ncbi.nlm.nih.gov/pubmed/31695729 http://dx.doi.org/10.1186/s13007-019-0507-8 |
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author | Duan, Bo Liu, Yating Gong, Yan Peng, Yi Wu, Xianting Zhu, Renshan Fang, Shenghui |
author_facet | Duan, Bo Liu, Yating Gong, Yan Peng, Yi Wu, Xianting Zhu, Renshan Fang, Shenghui |
author_sort | Duan, Bo |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6824110 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-68241102019-11-06 Remote estimation of rice LAI based on Fourier spectrum texture from UAV image Duan, Bo Liu, Yating Gong, Yan Peng, Yi Wu, Xianting Zhu, Renshan Fang, Shenghui Plant Methods Research 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. BioMed Central 2019-11-01 /pmc/articles/PMC6824110/ /pubmed/31695729 http://dx.doi.org/10.1186/s13007-019-0507-8 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Duan, Bo Liu, Yating Gong, Yan Peng, Yi Wu, Xianting Zhu, Renshan Fang, Shenghui Remote estimation of rice LAI based on Fourier spectrum texture from UAV image |
title | 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_short | 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 |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6824110/ https://www.ncbi.nlm.nih.gov/pubmed/31695729 http://dx.doi.org/10.1186/s13007-019-0507-8 |
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