Mapping Mosaic Virus in Sugarcane Based on Hyperspectral Images
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/JSTARS.2016.2635482 http://hdl.handle.net/11449/162537 |
Resumo: | The aim of this research was to develop a methodology involving aerial surveying using an unmanned aerial system (UAS), processing and analysis of images obtained by a hyperspectral camera, achieving results that enable discrimination and recognition of sugarcane plants infected with mosaic virus. It was necessary to characterize the spectral response of healthy and infected sugarcane plants in order to define the correct mode of operation for the hyperspectral camera, which provides many spectral band options for imaging but limits each image to 25 spectral bands. Spectral measurements of the leaves of infected and healthy sugarcane with a spectroradiometer were used to produce a spectral library. Once the most appropriate spectral bands had been selected, it was possible to configure the camera and carry out aerial surveying. The empirical line approach was adopted to obtain hemispherical conical reflectance factor values with a radiometric block adjustment to produce a mosaic suitable for the analysis. A classification based on spectral information divergence was applied and the results were evaluated by Kappa statistics. Areas of sugarcane infected with mosaic were identified from these hyperspectral images acquired by UAS and the results obtained had a high degree of accuracy. |
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Mapping Mosaic Virus in Sugarcane Based on Hyperspectral ImagesPhytosanitationprecision agricultureunmanned aerial system (UAS)The aim of this research was to develop a methodology involving aerial surveying using an unmanned aerial system (UAS), processing and analysis of images obtained by a hyperspectral camera, achieving results that enable discrimination and recognition of sugarcane plants infected with mosaic virus. It was necessary to characterize the spectral response of healthy and infected sugarcane plants in order to define the correct mode of operation for the hyperspectral camera, which provides many spectral band options for imaging but limits each image to 25 spectral bands. Spectral measurements of the leaves of infected and healthy sugarcane with a spectroradiometer were used to produce a spectral library. Once the most appropriate spectral bands had been selected, it was possible to configure the camera and carry out aerial surveying. The empirical line approach was adopted to obtain hemispherical conical reflectance factor values with a radiometric block adjustment to produce a mosaic suitable for the analysis. A classification based on spectral information divergence was applied and the results were evaluated by Kappa statistics. Areas of sugarcane infected with mosaic were identified from these hyperspectral images acquired by UAS and the results obtained had a high degree of accuracy.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Sao Paulo State Univ, Sch Sci & Technol, BR-19060900 Presidente Prudente, BrazilSao Paulo State Univ, Dept Cartog, Sch Sci & Technol, BR-19060900 Presidente Prudente, BrazilSao Paulo State Univ, Sch Sci & Technol, BR-19060900 Presidente Prudente, BrazilSao Paulo State Univ, Dept Cartog, Sch Sci & Technol, BR-19060900 Presidente Prudente, BrazilFAPESP: 2013/50426-4Ieee-inst Electrical Electronics Engineers IncUniversidade Estadual Paulista (Unesp)Moriya, Erika Akemi Saito [UNESP]Imai, Nilton Nobuhiro [UNESP]Tommaselli, Antonio Maria Garcia [UNESP]Miyoshi, Gabriela Takahashi [UNESP]2018-11-26T17:20:51Z2018-11-26T17:20:51Z2017-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article740-748application/pdfhttp://dx.doi.org/10.1109/JSTARS.2016.2635482Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 10, n. 2, p. 740-748, 2017.1939-1404http://hdl.handle.net/11449/16253710.1109/JSTARS.2016.2635482WOS:000395466700030WOS000395466700030.pdf0000-0003-0516-05672985771102505330Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIeee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing1,547info:eu-repo/semantics/openAccess2024-06-18T18:18:17Zoai:repositorio.unesp.br:11449/162537Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-06-18T18:18:17Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Mapping Mosaic Virus in Sugarcane Based on Hyperspectral Images |
title |
Mapping Mosaic Virus in Sugarcane Based on Hyperspectral Images |
spellingShingle |
Mapping Mosaic Virus in Sugarcane Based on Hyperspectral Images Moriya, Erika Akemi Saito [UNESP] Phytosanitation precision agriculture unmanned aerial system (UAS) |
title_short |
Mapping Mosaic Virus in Sugarcane Based on Hyperspectral Images |
title_full |
Mapping Mosaic Virus in Sugarcane Based on Hyperspectral Images |
title_fullStr |
Mapping Mosaic Virus in Sugarcane Based on Hyperspectral Images |
title_full_unstemmed |
Mapping Mosaic Virus in Sugarcane Based on Hyperspectral Images |
title_sort |
Mapping Mosaic Virus in Sugarcane Based on Hyperspectral Images |
author |
Moriya, Erika Akemi Saito [UNESP] |
author_facet |
Moriya, Erika Akemi Saito [UNESP] Imai, Nilton Nobuhiro [UNESP] Tommaselli, Antonio Maria Garcia [UNESP] Miyoshi, Gabriela Takahashi [UNESP] |
author_role |
author |
author2 |
Imai, Nilton Nobuhiro [UNESP] Tommaselli, Antonio Maria Garcia [UNESP] Miyoshi, Gabriela Takahashi [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Moriya, Erika Akemi Saito [UNESP] Imai, Nilton Nobuhiro [UNESP] Tommaselli, Antonio Maria Garcia [UNESP] Miyoshi, Gabriela Takahashi [UNESP] |
dc.subject.por.fl_str_mv |
Phytosanitation precision agriculture unmanned aerial system (UAS) |
topic |
Phytosanitation precision agriculture unmanned aerial system (UAS) |
description |
The aim of this research was to develop a methodology involving aerial surveying using an unmanned aerial system (UAS), processing and analysis of images obtained by a hyperspectral camera, achieving results that enable discrimination and recognition of sugarcane plants infected with mosaic virus. It was necessary to characterize the spectral response of healthy and infected sugarcane plants in order to define the correct mode of operation for the hyperspectral camera, which provides many spectral band options for imaging but limits each image to 25 spectral bands. Spectral measurements of the leaves of infected and healthy sugarcane with a spectroradiometer were used to produce a spectral library. Once the most appropriate spectral bands had been selected, it was possible to configure the camera and carry out aerial surveying. The empirical line approach was adopted to obtain hemispherical conical reflectance factor values with a radiometric block adjustment to produce a mosaic suitable for the analysis. A classification based on spectral information divergence was applied and the results were evaluated by Kappa statistics. Areas of sugarcane infected with mosaic were identified from these hyperspectral images acquired by UAS and the results obtained had a high degree of accuracy. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-02-01 2018-11-26T17:20:51Z 2018-11-26T17:20:51Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/JSTARS.2016.2635482 Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 10, n. 2, p. 740-748, 2017. 1939-1404 http://hdl.handle.net/11449/162537 10.1109/JSTARS.2016.2635482 WOS:000395466700030 WOS000395466700030.pdf 0000-0003-0516-0567 2985771102505330 |
url |
http://dx.doi.org/10.1109/JSTARS.2016.2635482 http://hdl.handle.net/11449/162537 |
identifier_str_mv |
Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 10, n. 2, p. 740-748, 2017. 1939-1404 10.1109/JSTARS.2016.2635482 WOS:000395466700030 WOS000395466700030.pdf 0000-0003-0516-0567 2985771102505330 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing 1,547 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
740-748 application/pdf |
dc.publisher.none.fl_str_mv |
Ieee-inst Electrical Electronics Engineers Inc |
publisher.none.fl_str_mv |
Ieee-inst Electrical Electronics Engineers Inc |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1803045552924917760 |