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Multispectral remote sensing for accurate acquisition of rice phenotypes: Impacts of radiometric calibration and unmanned aerial vehicle flying altitudes

As a promising method, unmanned aerial vehicle (UAV) multispectral remote sensing (RS) has been extensively studied in precision agriculture. However, there are numerous problems to be solved in the data acquisition and processing, which limit its application. In this study, the Micro-MCA12 camera w...

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Autores principales: Luo, Shanjun, Jiang, Xueqin, Yang, Kaili, Li, Yuanjin, Fang, Shenghui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9401905/
https://www.ncbi.nlm.nih.gov/pubmed/36035659
http://dx.doi.org/10.3389/fpls.2022.958106
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author Luo, Shanjun
Jiang, Xueqin
Yang, Kaili
Li, Yuanjin
Fang, Shenghui
author_facet Luo, Shanjun
Jiang, Xueqin
Yang, Kaili
Li, Yuanjin
Fang, Shenghui
author_sort Luo, Shanjun
collection PubMed
description As a promising method, unmanned aerial vehicle (UAV) multispectral remote sensing (RS) has been extensively studied in precision agriculture. However, there are numerous problems to be solved in the data acquisition and processing, which limit its application. In this study, the Micro-MCA12 camera was used to obtain images at different altitudes. The piecewise empirical line (PEL) method suitable for predicting the reflectance of different ground objects was proposed to accurately acquire the reflectance of multi-altitude images by comparing the performance of the conventional methods. Several commonly utilized vegetation indices (VIs) were computed to estimate the rice growth parameters and yield. Then the rice growth monitoring and yield prediction were implemented to verify and evaluate the effects of radiometric calibration methods (RCMs) and UAV flying altitudes (UAV-FAs). The results show that the variation trends of reflectance and VIs are significantly different due to the change in component proportion observed at different altitudes. Except for the milking stage, the reflectance and VIs in other periods fluctuated greatly in the first 100 m and remained stable thereafter. This phenomenon was determined by the field of view of the sensor and the characteristic of the ground object. The selection of an appropriate calibration method was essential as a result of the marked differences in the rice phenotypes estimation accuracy based on different RCMs. There were pronounced differences in the accuracy of rice growth monitoring and yield estimation based on the 50 and 100 m-based variables, and the altitudes above 100 m had no notable effect on the results. This study can provide a reference for the application of UAV RS technology in precision agriculture and the accurate acquisition of crop phenotypes.
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spelling pubmed-94019052022-08-25 Multispectral remote sensing for accurate acquisition of rice phenotypes: Impacts of radiometric calibration and unmanned aerial vehicle flying altitudes Luo, Shanjun Jiang, Xueqin Yang, Kaili Li, Yuanjin Fang, Shenghui Front Plant Sci Plant Science As a promising method, unmanned aerial vehicle (UAV) multispectral remote sensing (RS) has been extensively studied in precision agriculture. However, there are numerous problems to be solved in the data acquisition and processing, which limit its application. In this study, the Micro-MCA12 camera was used to obtain images at different altitudes. The piecewise empirical line (PEL) method suitable for predicting the reflectance of different ground objects was proposed to accurately acquire the reflectance of multi-altitude images by comparing the performance of the conventional methods. Several commonly utilized vegetation indices (VIs) were computed to estimate the rice growth parameters and yield. Then the rice growth monitoring and yield prediction were implemented to verify and evaluate the effects of radiometric calibration methods (RCMs) and UAV flying altitudes (UAV-FAs). The results show that the variation trends of reflectance and VIs are significantly different due to the change in component proportion observed at different altitudes. Except for the milking stage, the reflectance and VIs in other periods fluctuated greatly in the first 100 m and remained stable thereafter. This phenomenon was determined by the field of view of the sensor and the characteristic of the ground object. The selection of an appropriate calibration method was essential as a result of the marked differences in the rice phenotypes estimation accuracy based on different RCMs. There were pronounced differences in the accuracy of rice growth monitoring and yield estimation based on the 50 and 100 m-based variables, and the altitudes above 100 m had no notable effect on the results. This study can provide a reference for the application of UAV RS technology in precision agriculture and the accurate acquisition of crop phenotypes. Frontiers Media S.A. 2022-08-10 /pmc/articles/PMC9401905/ /pubmed/36035659 http://dx.doi.org/10.3389/fpls.2022.958106 Text en Copyright © 2022 Luo, Jiang, Yang, Li and Fang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Luo, Shanjun
Jiang, Xueqin
Yang, Kaili
Li, Yuanjin
Fang, Shenghui
Multispectral remote sensing for accurate acquisition of rice phenotypes: Impacts of radiometric calibration and unmanned aerial vehicle flying altitudes
title Multispectral remote sensing for accurate acquisition of rice phenotypes: Impacts of radiometric calibration and unmanned aerial vehicle flying altitudes
title_full Multispectral remote sensing for accurate acquisition of rice phenotypes: Impacts of radiometric calibration and unmanned aerial vehicle flying altitudes
title_fullStr Multispectral remote sensing for accurate acquisition of rice phenotypes: Impacts of radiometric calibration and unmanned aerial vehicle flying altitudes
title_full_unstemmed Multispectral remote sensing for accurate acquisition of rice phenotypes: Impacts of radiometric calibration and unmanned aerial vehicle flying altitudes
title_short Multispectral remote sensing for accurate acquisition of rice phenotypes: Impacts of radiometric calibration and unmanned aerial vehicle flying altitudes
title_sort multispectral remote sensing for accurate acquisition of rice phenotypes: impacts of radiometric calibration and unmanned aerial vehicle flying altitudes
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9401905/
https://www.ncbi.nlm.nih.gov/pubmed/36035659
http://dx.doi.org/10.3389/fpls.2022.958106
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