IDENTIFICATION OF MAIZE LODGING: A CASE STUDY USING A REMOTELY PILOTED AIRCRAFT SYSTEM

Detalhes bibliográficos
Autor(a) principal: Acorsi,Matheus G.
Data de Publicação: 2019
Outros Autores: Martello,Maurício, Angnes,Graciele
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Engenharia Agrícola
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000800066
Resumo: ABSTRACT A common agricultural problem in many regions of Brazil is maize lodging, as a consequence of strong winds and rain which impacts on crop growth and yield. However, collecting data using ground-based, manual field measurement methods is inefficient. An emerging tool is the Remotely Piloted Aircraft System (RPAS), capable of delivering spatial data with high resolution and flexible periodicity. In this study, the potential to detect the maize lodging using crop surface models derived from RPAS was assessed. Our RPA-based approach uses a quantitative threshold to determine lodging percentage. The threshold values of plant height, used to detect the occurrence of lodging, were based on fixed and variable values. The validation of percentage lodging was performed using the RGB orthomosaic. The derived lodging estimates showed a very high correlation to the reference data. High correlations were observed for the fixed threshold at 60% (R2 = 0.93, RSME = 8.72%) and the variable thresholds, Jenks natural breaks and iso-clusters (R2 = 0.92, RSME = 8.89% and R2= 0.92, RSME = 9%, respectively). This study demonstrated the potential of the use of this technique, reducing the subjectivity of ground-based evaluation and the laborious traditional technique of lodging inference.
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spelling IDENTIFICATION OF MAIZE LODGING: A CASE STUDY USING A REMOTELY PILOTED AIRCRAFT SYSTEMCrop surface modelstructure from motioncanopy heightRGBABSTRACT A common agricultural problem in many regions of Brazil is maize lodging, as a consequence of strong winds and rain which impacts on crop growth and yield. However, collecting data using ground-based, manual field measurement methods is inefficient. An emerging tool is the Remotely Piloted Aircraft System (RPAS), capable of delivering spatial data with high resolution and flexible periodicity. In this study, the potential to detect the maize lodging using crop surface models derived from RPAS was assessed. Our RPA-based approach uses a quantitative threshold to determine lodging percentage. The threshold values of plant height, used to detect the occurrence of lodging, were based on fixed and variable values. The validation of percentage lodging was performed using the RGB orthomosaic. The derived lodging estimates showed a very high correlation to the reference data. High correlations were observed for the fixed threshold at 60% (R2 = 0.93, RSME = 8.72%) and the variable thresholds, Jenks natural breaks and iso-clusters (R2 = 0.92, RSME = 8.89% and R2= 0.92, RSME = 9%, respectively). This study demonstrated the potential of the use of this technique, reducing the subjectivity of ground-based evaluation and the laborious traditional technique of lodging inference.Associação Brasileira de Engenharia Agrícola2019-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000800066Engenharia Agrícola v.39 n.spe 2019reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-eng.agric.v39nep66-73/2019info:eu-repo/semantics/openAccessAcorsi,Matheus G.Martello,MaurícioAngnes,Gracieleeng2019-09-05T00:00:00Zoai:scielo:S0100-69162019000800066Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2019-09-05T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false
dc.title.none.fl_str_mv IDENTIFICATION OF MAIZE LODGING: A CASE STUDY USING A REMOTELY PILOTED AIRCRAFT SYSTEM
title IDENTIFICATION OF MAIZE LODGING: A CASE STUDY USING A REMOTELY PILOTED AIRCRAFT SYSTEM
spellingShingle IDENTIFICATION OF MAIZE LODGING: A CASE STUDY USING A REMOTELY PILOTED AIRCRAFT SYSTEM
Acorsi,Matheus G.
Crop surface model
structure from motion
canopy height
RGB
title_short IDENTIFICATION OF MAIZE LODGING: A CASE STUDY USING A REMOTELY PILOTED AIRCRAFT SYSTEM
title_full IDENTIFICATION OF MAIZE LODGING: A CASE STUDY USING A REMOTELY PILOTED AIRCRAFT SYSTEM
title_fullStr IDENTIFICATION OF MAIZE LODGING: A CASE STUDY USING A REMOTELY PILOTED AIRCRAFT SYSTEM
title_full_unstemmed IDENTIFICATION OF MAIZE LODGING: A CASE STUDY USING A REMOTELY PILOTED AIRCRAFT SYSTEM
title_sort IDENTIFICATION OF MAIZE LODGING: A CASE STUDY USING A REMOTELY PILOTED AIRCRAFT SYSTEM
author Acorsi,Matheus G.
author_facet Acorsi,Matheus G.
Martello,Maurício
Angnes,Graciele
author_role author
author2 Martello,Maurício
Angnes,Graciele
author2_role author
author
dc.contributor.author.fl_str_mv Acorsi,Matheus G.
Martello,Maurício
Angnes,Graciele
dc.subject.por.fl_str_mv Crop surface model
structure from motion
canopy height
RGB
topic Crop surface model
structure from motion
canopy height
RGB
description ABSTRACT A common agricultural problem in many regions of Brazil is maize lodging, as a consequence of strong winds and rain which impacts on crop growth and yield. However, collecting data using ground-based, manual field measurement methods is inefficient. An emerging tool is the Remotely Piloted Aircraft System (RPAS), capable of delivering spatial data with high resolution and flexible periodicity. In this study, the potential to detect the maize lodging using crop surface models derived from RPAS was assessed. Our RPA-based approach uses a quantitative threshold to determine lodging percentage. The threshold values of plant height, used to detect the occurrence of lodging, were based on fixed and variable values. The validation of percentage lodging was performed using the RGB orthomosaic. The derived lodging estimates showed a very high correlation to the reference data. High correlations were observed for the fixed threshold at 60% (R2 = 0.93, RSME = 8.72%) and the variable thresholds, Jenks natural breaks and iso-clusters (R2 = 0.92, RSME = 8.89% and R2= 0.92, RSME = 9%, respectively). This study demonstrated the potential of the use of this technique, reducing the subjectivity of ground-based evaluation and the laborious traditional technique of lodging inference.
publishDate 2019
dc.date.none.fl_str_mv 2019-09-01
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=S0100-69162019000800066
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000800066
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1809-4430-eng.agric.v39nep66-73/2019
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 Associação Brasileira de Engenharia Agrícola
publisher.none.fl_str_mv Associação Brasileira de Engenharia Agrícola
dc.source.none.fl_str_mv Engenharia Agrícola v.39 n.spe 2019
reponame:Engenharia Agrícola
instname:Associação Brasileira de Engenharia Agrícola (SBEA)
instacron:SBEA
instname_str Associação Brasileira de Engenharia Agrícola (SBEA)
instacron_str SBEA
institution SBEA
reponame_str Engenharia Agrícola
collection Engenharia Agrícola
repository.name.fl_str_mv Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)
repository.mail.fl_str_mv revistasbea@sbea.org.br||sbea@sbea.org.br
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