Orbital spectral variables, growth analysis and sugarcane yield

Detalhes bibliográficos
Autor(a) principal: Simões,Maurício dos Santos
Data de Publicação: 2009
Outros Autores: Rocha,Jansle Vieira, Lamparelli,Rubens Augusto Camargo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162009000400004
Resumo: Temporal analysis of crop development in commercial fields requires tools for large area monitoring, such as remote sensing. This paper describes the temporal evolution of sugar cane biophysical parameters such as total biomass (BMT), yield (TSS), leaf area index (LAI), and number of plants per linear meter (NPM) correlated to Landsat data. During the 2000 and 2001 cropping seasons, a commercial sugarcane field in Araras, São Paulo state, Brazil, planted with the SP80-1842 sugarcane variety in the 4th and 5th cuts, was monitored using nine Landsat images. Spectral data were correlated with agronomic data, obtained simultaneously to the imagery acquisition. Two methodologies were used to collect spectral data from the images: four pixels (2 × 2) window and average of total pixels in the field. Linear and multiple regression analysis was used to study the spectral behavior of the plants and to correlate with agronomic variables (days after harvest-DAC, LAI, NPM, BMT and TSS). No difference was observed between the methodologies to collect spectral data. The best models to describe the spectral crop development in relation to DAC were the quadratic and cubic models. Ratio vegetation index and normalized difference vegetation index demonstrated correlation with DAC, band 3 (B3) was correlated with LAI, and NDVI was well correlated with TSS and BMT. The best fit curves to estimate TSS and BMT presented r² between 0.68 and 0.97, suggesting good potential in using orbital spectral data to monitor sugarcane fields.
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spelling Orbital spectral variables, growth analysis and sugarcane yieldbiomassleaf area indexcrop development analysisspectral behaviorTemporal analysis of crop development in commercial fields requires tools for large area monitoring, such as remote sensing. This paper describes the temporal evolution of sugar cane biophysical parameters such as total biomass (BMT), yield (TSS), leaf area index (LAI), and number of plants per linear meter (NPM) correlated to Landsat data. During the 2000 and 2001 cropping seasons, a commercial sugarcane field in Araras, São Paulo state, Brazil, planted with the SP80-1842 sugarcane variety in the 4th and 5th cuts, was monitored using nine Landsat images. Spectral data were correlated with agronomic data, obtained simultaneously to the imagery acquisition. Two methodologies were used to collect spectral data from the images: four pixels (2 × 2) window and average of total pixels in the field. Linear and multiple regression analysis was used to study the spectral behavior of the plants and to correlate with agronomic variables (days after harvest-DAC, LAI, NPM, BMT and TSS). No difference was observed between the methodologies to collect spectral data. The best models to describe the spectral crop development in relation to DAC were the quadratic and cubic models. Ratio vegetation index and normalized difference vegetation index demonstrated correlation with DAC, band 3 (B3) was correlated with LAI, and NDVI was well correlated with TSS and BMT. The best fit curves to estimate TSS and BMT presented r² between 0.68 and 0.97, suggesting good potential in using orbital spectral data to monitor sugarcane fields.Escola Superior de Agricultura "Luiz de Queiroz"2009-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162009000400004Scientia Agricola v.66 n.4 2009reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USP10.1590/S0103-90162009000400004info:eu-repo/semantics/openAccessSimões,Maurício dos SantosRocha,Jansle VieiraLamparelli,Rubens Augusto Camargoeng2009-08-07T00:00:00Zoai:scielo:S0103-90162009000400004Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2009-08-07T00:00Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Orbital spectral variables, growth analysis and sugarcane yield
title Orbital spectral variables, growth analysis and sugarcane yield
spellingShingle Orbital spectral variables, growth analysis and sugarcane yield
Simões,Maurício dos Santos
biomass
leaf area index
crop development analysis
spectral behavior
title_short Orbital spectral variables, growth analysis and sugarcane yield
title_full Orbital spectral variables, growth analysis and sugarcane yield
title_fullStr Orbital spectral variables, growth analysis and sugarcane yield
title_full_unstemmed Orbital spectral variables, growth analysis and sugarcane yield
title_sort Orbital spectral variables, growth analysis and sugarcane yield
author Simões,Maurício dos Santos
author_facet Simões,Maurício dos Santos
Rocha,Jansle Vieira
Lamparelli,Rubens Augusto Camargo
author_role author
author2 Rocha,Jansle Vieira
Lamparelli,Rubens Augusto Camargo
author2_role author
author
dc.contributor.author.fl_str_mv Simões,Maurício dos Santos
Rocha,Jansle Vieira
Lamparelli,Rubens Augusto Camargo
dc.subject.por.fl_str_mv biomass
leaf area index
crop development analysis
spectral behavior
topic biomass
leaf area index
crop development analysis
spectral behavior
description Temporal analysis of crop development in commercial fields requires tools for large area monitoring, such as remote sensing. This paper describes the temporal evolution of sugar cane biophysical parameters such as total biomass (BMT), yield (TSS), leaf area index (LAI), and number of plants per linear meter (NPM) correlated to Landsat data. During the 2000 and 2001 cropping seasons, a commercial sugarcane field in Araras, São Paulo state, Brazil, planted with the SP80-1842 sugarcane variety in the 4th and 5th cuts, was monitored using nine Landsat images. Spectral data were correlated with agronomic data, obtained simultaneously to the imagery acquisition. Two methodologies were used to collect spectral data from the images: four pixels (2 × 2) window and average of total pixels in the field. Linear and multiple regression analysis was used to study the spectral behavior of the plants and to correlate with agronomic variables (days after harvest-DAC, LAI, NPM, BMT and TSS). No difference was observed between the methodologies to collect spectral data. The best models to describe the spectral crop development in relation to DAC were the quadratic and cubic models. Ratio vegetation index and normalized difference vegetation index demonstrated correlation with DAC, band 3 (B3) was correlated with LAI, and NDVI was well correlated with TSS and BMT. The best fit curves to estimate TSS and BMT presented r² between 0.68 and 0.97, suggesting good potential in using orbital spectral data to monitor sugarcane fields.
publishDate 2009
dc.date.none.fl_str_mv 2009-08-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162009000400004
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162009000400004
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0103-90162009000400004
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Escola Superior de Agricultura "Luiz de Queiroz"
publisher.none.fl_str_mv Escola Superior de Agricultura "Luiz de Queiroz"
dc.source.none.fl_str_mv Scientia Agricola v.66 n.4 2009
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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