Assessing biophysical variable parameters of bean crop with hyperspectral measurements

Detalhes bibliográficos
Autor(a) principal: Monteiro, Priscylla Ferraz Câmara
Data de Publicação: 2012
Outros Autores: Angulo Filho, Rubens, Xavier, Alexandre Cândido, Monteiro, Rodrigo Otávio Câmara
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: https://www.revistas.usp.br/sa/article/view/22751
Resumo: Recently high spectral resolution sensors have been developed, which allow new and more advanced applications in agriculture. Motivated by the increasing importance of hyperspectral remote sensing data, the need for research is important to define optimal wavebands to estimate biophysical parameters of crop. The use of narrow band vegetation indices (VI) derived from hyperspectral measurements acquired by a field spectrometer was evaluated to estimate bean (Phaseolus vulgaris L.) grain yield, plant height and leaf area index (LAI). Field canopy reflectance measurements were acquired at six bean growth stages over 48 plots with four water levels (179.5; 256.5; 357.5 and 406.2 mm) and tree nitrogen rates (0; 80 and 160 kg ha-1) and four replicates. The following VI was analyzed: OSNBR (optimum simple narrow-band reflectivity); NB_NDVI (narrow-band normalized difference vegetation index) and NDVI (normalized difference index). The vegetation indices investigated (OSNBR, NB_NDVI and NDVI) were efficient to estimate LAI, plant height and grain yield. During all crop development, the best correlations between biophysical variables and spectral variables were observed on V4 (the third trifoliolate leaves were unfolded in 50 % of plants) and R6 (plants developed first flowers in 50 % of plants) stages, according to the variable analyzed.
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spelling Assessing biophysical variable parameters of bean crop with hyperspectral measurements hyperspectral remote sensingspectroradiometryvegetation indices Recently high spectral resolution sensors have been developed, which allow new and more advanced applications in agriculture. Motivated by the increasing importance of hyperspectral remote sensing data, the need for research is important to define optimal wavebands to estimate biophysical parameters of crop. The use of narrow band vegetation indices (VI) derived from hyperspectral measurements acquired by a field spectrometer was evaluated to estimate bean (Phaseolus vulgaris L.) grain yield, plant height and leaf area index (LAI). Field canopy reflectance measurements were acquired at six bean growth stages over 48 plots with four water levels (179.5; 256.5; 357.5 and 406.2 mm) and tree nitrogen rates (0; 80 and 160 kg ha-1) and four replicates. The following VI was analyzed: OSNBR (optimum simple narrow-band reflectivity); NB_NDVI (narrow-band normalized difference vegetation index) and NDVI (normalized difference index). The vegetation indices investigated (OSNBR, NB_NDVI and NDVI) were efficient to estimate LAI, plant height and grain yield. During all crop development, the best correlations between biophysical variables and spectral variables were observed on V4 (the third trifoliolate leaves were unfolded in 50 % of plants) and R6 (plants developed first flowers in 50 % of plants) stages, according to the variable analyzed. Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2012-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/2275110.1590/S0103-90162012000200001Scientia Agricola; v. 69 n. 2 (2012); 87-94Scientia Agricola; Vol. 69 No. 2 (2012); 87-94Scientia Agricola; Vol. 69 Núm. 2 (2012); 87-941678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/22751/24775Copyright (c) 2015 Scientia Agricolainfo:eu-repo/semantics/openAccessMonteiro, Priscylla Ferraz CâmaraAngulo Filho, RubensXavier, Alexandre CândidoMonteiro, Rodrigo Otávio Câmara2015-07-07T19:14:45Zoai:revistas.usp.br:article/22751Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2015-07-07T19:14:45Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Assessing biophysical variable parameters of bean crop with hyperspectral measurements
title Assessing biophysical variable parameters of bean crop with hyperspectral measurements
spellingShingle Assessing biophysical variable parameters of bean crop with hyperspectral measurements
Monteiro, Priscylla Ferraz Câmara
hyperspectral remote sensing
spectroradiometry
vegetation indices
title_short Assessing biophysical variable parameters of bean crop with hyperspectral measurements
title_full Assessing biophysical variable parameters of bean crop with hyperspectral measurements
title_fullStr Assessing biophysical variable parameters of bean crop with hyperspectral measurements
title_full_unstemmed Assessing biophysical variable parameters of bean crop with hyperspectral measurements
title_sort Assessing biophysical variable parameters of bean crop with hyperspectral measurements
author Monteiro, Priscylla Ferraz Câmara
author_facet Monteiro, Priscylla Ferraz Câmara
Angulo Filho, Rubens
Xavier, Alexandre Cândido
Monteiro, Rodrigo Otávio Câmara
author_role author
author2 Angulo Filho, Rubens
Xavier, Alexandre Cândido
Monteiro, Rodrigo Otávio Câmara
author2_role author
author
author
dc.contributor.author.fl_str_mv Monteiro, Priscylla Ferraz Câmara
Angulo Filho, Rubens
Xavier, Alexandre Cândido
Monteiro, Rodrigo Otávio Câmara
dc.subject.por.fl_str_mv hyperspectral remote sensing
spectroradiometry
vegetation indices
topic hyperspectral remote sensing
spectroradiometry
vegetation indices
description Recently high spectral resolution sensors have been developed, which allow new and more advanced applications in agriculture. Motivated by the increasing importance of hyperspectral remote sensing data, the need for research is important to define optimal wavebands to estimate biophysical parameters of crop. The use of narrow band vegetation indices (VI) derived from hyperspectral measurements acquired by a field spectrometer was evaluated to estimate bean (Phaseolus vulgaris L.) grain yield, plant height and leaf area index (LAI). Field canopy reflectance measurements were acquired at six bean growth stages over 48 plots with four water levels (179.5; 256.5; 357.5 and 406.2 mm) and tree nitrogen rates (0; 80 and 160 kg ha-1) and four replicates. The following VI was analyzed: OSNBR (optimum simple narrow-band reflectivity); NB_NDVI (narrow-band normalized difference vegetation index) and NDVI (normalized difference index). The vegetation indices investigated (OSNBR, NB_NDVI and NDVI) were efficient to estimate LAI, plant height and grain yield. During all crop development, the best correlations between biophysical variables and spectral variables were observed on V4 (the third trifoliolate leaves were unfolded in 50 % of plants) and R6 (plants developed first flowers in 50 % of plants) stages, according to the variable analyzed.
publishDate 2012
dc.date.none.fl_str_mv 2012-04-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.revistas.usp.br/sa/article/view/22751
10.1590/S0103-90162012000200001
url https://www.revistas.usp.br/sa/article/view/22751
identifier_str_mv 10.1590/S0103-90162012000200001
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://www.revistas.usp.br/sa/article/view/22751/24775
dc.rights.driver.fl_str_mv Copyright (c) 2015 Scientia Agricola
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2015 Scientia Agricola
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
dc.source.none.fl_str_mv Scientia Agricola; v. 69 n. 2 (2012); 87-94
Scientia Agricola; Vol. 69 No. 2 (2012); 87-94
Scientia Agricola; Vol. 69 Núm. 2 (2012); 87-94
1678-992X
0103-9016
reponame:Scientia Agrícola (Online)
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Scientia Agrícola (Online)
collection Scientia Agrícola (Online)
repository.name.fl_str_mv Scientia Agrícola (Online) - Universidade de São Paulo (USP)
repository.mail.fl_str_mv scientia@usp.br||alleoni@usp.br
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