Using remote sensing to map in-field variability of peanut maturity

Detalhes bibliográficos
Autor(a) principal: Santos, A. F. [UNESP]
Data de Publicação: 2019
Outros Autores: Lacerda, L. N., Gobbo, S., Tofannin, A., Silva, R. P. [UNESP], Vellidis, G.
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.3920/978-90-8686-888-9_75
http://hdl.handle.net/11449/198036
Resumo: A study was conducted to assess if vegetation indices (VIs) could be used as indicators of peanut maturity. A 24 ha block of a rainfed field with clearly visible soil and crop variability was used. An unmanned aerial vehicle (UAV) equipped with a multispectral camera captured spectral reflectance from the peanut canopy. The reflectance data were used to evaluate several VIs as potential indicators of peanut maturity. Pearson's correlation and linear regression were used to evaluate the response of the VIs as well as the sensitivity of individual reflectance bands to peanut maturity. The red edge band was the most sensitive. The most responsive VIs were the non-linear index (NLI) and the modified non-linear index (MNLI) when red edge reflectance was substituted for red reflectance.
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spelling Using remote sensing to map in-field variability of peanut maturityMultispectral imagesRed edgeReflectanceUAVVegetation indexA study was conducted to assess if vegetation indices (VIs) could be used as indicators of peanut maturity. A 24 ha block of a rainfed field with clearly visible soil and crop variability was used. An unmanned aerial vehicle (UAV) equipped with a multispectral camera captured spectral reflectance from the peanut canopy. The reflectance data were used to evaluate several VIs as potential indicators of peanut maturity. Pearson's correlation and linear regression were used to evaluate the response of the VIs as well as the sensitivity of individual reflectance bands to peanut maturity. The red edge band was the most sensitive. The most responsive VIs were the non-linear index (NLI) and the modified non-linear index (MNLI) when red edge reflectance was substituted for red reflectance.University of Wisconsin - SuperiorUniversity of Georgia Tifton CampusSão Paulo State University (UNESP) Jaboticabal CampusSão Paulo State University (UNESP) Jaboticabal CampusTifton CampusUniversidade Estadual Paulista (Unesp)Santos, A. F. [UNESP]Lacerda, L. N.Gobbo, S.Tofannin, A.Silva, R. P. [UNESP]Vellidis, G.2020-12-12T00:57:13Z2020-12-12T00:57:13Z2019-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject605-611http://dx.doi.org/10.3920/978-90-8686-888-9_75Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019, p. 605-611.http://hdl.handle.net/11449/19803610.3920/978-90-8686-888-9_752-s2.0-85073749480Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPrecision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019info:eu-repo/semantics/openAccess2021-10-23T07:59:21Zoai:repositorio.unesp.br:11449/198036Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:52:09.391784Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Using remote sensing to map in-field variability of peanut maturity
title Using remote sensing to map in-field variability of peanut maturity
spellingShingle Using remote sensing to map in-field variability of peanut maturity
Santos, A. F. [UNESP]
Multispectral images
Red edge
Reflectance
UAV
Vegetation index
title_short Using remote sensing to map in-field variability of peanut maturity
title_full Using remote sensing to map in-field variability of peanut maturity
title_fullStr Using remote sensing to map in-field variability of peanut maturity
title_full_unstemmed Using remote sensing to map in-field variability of peanut maturity
title_sort Using remote sensing to map in-field variability of peanut maturity
author Santos, A. F. [UNESP]
author_facet Santos, A. F. [UNESP]
Lacerda, L. N.
Gobbo, S.
Tofannin, A.
Silva, R. P. [UNESP]
Vellidis, G.
author_role author
author2 Lacerda, L. N.
Gobbo, S.
Tofannin, A.
Silva, R. P. [UNESP]
Vellidis, G.
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Tifton Campus
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Santos, A. F. [UNESP]
Lacerda, L. N.
Gobbo, S.
Tofannin, A.
Silva, R. P. [UNESP]
Vellidis, G.
dc.subject.por.fl_str_mv Multispectral images
Red edge
Reflectance
UAV
Vegetation index
topic Multispectral images
Red edge
Reflectance
UAV
Vegetation index
description A study was conducted to assess if vegetation indices (VIs) could be used as indicators of peanut maturity. A 24 ha block of a rainfed field with clearly visible soil and crop variability was used. An unmanned aerial vehicle (UAV) equipped with a multispectral camera captured spectral reflectance from the peanut canopy. The reflectance data were used to evaluate several VIs as potential indicators of peanut maturity. Pearson's correlation and linear regression were used to evaluate the response of the VIs as well as the sensitivity of individual reflectance bands to peanut maturity. The red edge band was the most sensitive. The most responsive VIs were the non-linear index (NLI) and the modified non-linear index (MNLI) when red edge reflectance was substituted for red reflectance.
publishDate 2019
dc.date.none.fl_str_mv 2019-01-01
2020-12-12T00:57:13Z
2020-12-12T00:57:13Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.3920/978-90-8686-888-9_75
Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019, p. 605-611.
http://hdl.handle.net/11449/198036
10.3920/978-90-8686-888-9_75
2-s2.0-85073749480
url http://dx.doi.org/10.3920/978-90-8686-888-9_75
http://hdl.handle.net/11449/198036
identifier_str_mv Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019, p. 605-611.
10.3920/978-90-8686-888-9_75
2-s2.0-85073749480
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 605-611
dc.source.none.fl_str_mv Scopus
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
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