Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Duan, Bo, Liu, Yating, Gong, Yan, Peng, Yi, Wu, Xianting, Zhu, Renshan, Fang, Shenghui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
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
_version_ 1783464675269148672
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
work_keys_str_mv AT duanbo remoteestimationofricelaibasedonfourierspectrumtexturefromuavimage
AT liuyating remoteestimationofricelaibasedonfourierspectrumtexturefromuavimage
AT gongyan remoteestimationofricelaibasedonfourierspectrumtexturefromuavimage
AT pengyi remoteestimationofricelaibasedonfourierspectrumtexturefromuavimage
AT wuxianting remoteestimationofricelaibasedonfourierspectrumtexturefromuavimage
AT zhurenshan remoteestimationofricelaibasedonfourierspectrumtexturefromuavimage
AT fangshenghui remoteestimationofricelaibasedonfourierspectrumtexturefromuavimage