ESTIMATION OF MAIZE BIOMASS USING UNMANNED AERIAL VEHICLES
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Engenharia Agrícola |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000600744 |
Resumo: | ABSTRACT Unmanned aerial vehicles (UAVs) are a promising tool for technology development and transfer and for the economic success of the agricultural sector. The objective of this study is to assess the validity of biomass estimation in a commercial maize plantation using aerial images obtained by a UAV. The proposed methodology involved analyzing images acquired in scheduled flights, processing orthophoto (georeferenced image) data, evaluating digital terrain elevation models, and assessing the quality of dense point clouds. Data were collected using two cameras, one with a 16-megapixel flat lens and the other with a 12-megapixel fish-eye lens coupled to a UAV, at two flight altitudes (30 and 60 meters) over hybrid maize (AG1051) crop irrigated by center pivot in the municipality of Limoeiro do Norte, Ceará, Brazil. Crop biomass was estimated in 1 m2 plots sampled randomly, and data were validated by interpreting aerial images of target areas. The measurements of biomass using UAV-based aerial images were promising. The estimated values were more accurate using the fish-eye lens at 30 m altitude, corresponding to 2.97 kg m-2, which is very close to the values measured in the field (2.92 kg m-2). |
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Engenharia Agrícola |
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ESTIMATION OF MAIZE BIOMASS USING UNMANNED AERIAL VEHICLESprecision agricultureStructure from Motionunmanned aerial vehiclesZea mays LABSTRACT Unmanned aerial vehicles (UAVs) are a promising tool for technology development and transfer and for the economic success of the agricultural sector. The objective of this study is to assess the validity of biomass estimation in a commercial maize plantation using aerial images obtained by a UAV. The proposed methodology involved analyzing images acquired in scheduled flights, processing orthophoto (georeferenced image) data, evaluating digital terrain elevation models, and assessing the quality of dense point clouds. Data were collected using two cameras, one with a 16-megapixel flat lens and the other with a 12-megapixel fish-eye lens coupled to a UAV, at two flight altitudes (30 and 60 meters) over hybrid maize (AG1051) crop irrigated by center pivot in the municipality of Limoeiro do Norte, Ceará, Brazil. Crop biomass was estimated in 1 m2 plots sampled randomly, and data were validated by interpreting aerial images of target areas. The measurements of biomass using UAV-based aerial images were promising. The estimated values were more accurate using the fish-eye lens at 30 m altitude, corresponding to 2.97 kg m-2, which is very close to the values measured in the field (2.92 kg m-2).Associação Brasileira de Engenharia Agrícola2019-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000600744Engenharia Agrícola v.39 n.6 2019reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-eng.agric.v39n6p744-752/2019info:eu-repo/semantics/openAccessCalou,Vinícius B. C.Teixeira,Adunias dos S.Moreira,Luis C. J.Rocha Neto,Odílio C. daSilva,José A. daeng2020-02-13T00:00:00Zoai:scielo:S0100-69162019000600744Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2020-02-13T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false |
dc.title.none.fl_str_mv |
ESTIMATION OF MAIZE BIOMASS USING UNMANNED AERIAL VEHICLES |
title |
ESTIMATION OF MAIZE BIOMASS USING UNMANNED AERIAL VEHICLES |
spellingShingle |
ESTIMATION OF MAIZE BIOMASS USING UNMANNED AERIAL VEHICLES Calou,Vinícius B. C. precision agriculture Structure from Motion unmanned aerial vehicles Zea mays L |
title_short |
ESTIMATION OF MAIZE BIOMASS USING UNMANNED AERIAL VEHICLES |
title_full |
ESTIMATION OF MAIZE BIOMASS USING UNMANNED AERIAL VEHICLES |
title_fullStr |
ESTIMATION OF MAIZE BIOMASS USING UNMANNED AERIAL VEHICLES |
title_full_unstemmed |
ESTIMATION OF MAIZE BIOMASS USING UNMANNED AERIAL VEHICLES |
title_sort |
ESTIMATION OF MAIZE BIOMASS USING UNMANNED AERIAL VEHICLES |
author |
Calou,Vinícius B. C. |
author_facet |
Calou,Vinícius B. C. Teixeira,Adunias dos S. Moreira,Luis C. J. Rocha Neto,Odílio C. da Silva,José A. da |
author_role |
author |
author2 |
Teixeira,Adunias dos S. Moreira,Luis C. J. Rocha Neto,Odílio C. da Silva,José A. da |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Calou,Vinícius B. C. Teixeira,Adunias dos S. Moreira,Luis C. J. Rocha Neto,Odílio C. da Silva,José A. da |
dc.subject.por.fl_str_mv |
precision agriculture Structure from Motion unmanned aerial vehicles Zea mays L |
topic |
precision agriculture Structure from Motion unmanned aerial vehicles Zea mays L |
description |
ABSTRACT Unmanned aerial vehicles (UAVs) are a promising tool for technology development and transfer and for the economic success of the agricultural sector. The objective of this study is to assess the validity of biomass estimation in a commercial maize plantation using aerial images obtained by a UAV. The proposed methodology involved analyzing images acquired in scheduled flights, processing orthophoto (georeferenced image) data, evaluating digital terrain elevation models, and assessing the quality of dense point clouds. Data were collected using two cameras, one with a 16-megapixel flat lens and the other with a 12-megapixel fish-eye lens coupled to a UAV, at two flight altitudes (30 and 60 meters) over hybrid maize (AG1051) crop irrigated by center pivot in the municipality of Limoeiro do Norte, Ceará, Brazil. Crop biomass was estimated in 1 m2 plots sampled randomly, and data were validated by interpreting aerial images of target areas. The measurements of biomass using UAV-based aerial images were promising. The estimated values were more accurate using the fish-eye lens at 30 m altitude, corresponding to 2.97 kg m-2, which is very close to the values measured in the field (2.92 kg m-2). |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-12-01 |
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=S0100-69162019000600744 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000600744 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1809-4430-eng.agric.v39n6p744-752/2019 |
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.6 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 |
_version_ |
1752126274471460864 |