Estimate of vigor classes of Brachiaria ruziziensis using sensors boarded on UAV plataform.
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
Texto Completo: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1138479 https://dx.doi.org/10.22161/ijaers.812.37 |
Resumo: | Traditional procedures for biomass estimation usually use destructive methods with great demands on time, resources, and labor. The development of models for automated estimation of pasture biomass, particularly from images captured by Unmanned Aerial Vehicle (UAV), in addition to high spatiotemporal resolution combined with flexibility in image acquisition, provides agility, the economy of resources, and labor. The objective of this work was to establish a technical feasibility study for the use of multispectral sensors onboard an Unmanned Aerial Vehicle (UAV) to estimate the vigor classes of Brachiaria ruziziensis pastures. For this purpose, imaging cameras in the visible (RGB), near-infrared and red edge ranges were used for continuous monitoring of 20 pasture paddocks with an area of 1,350 m2 each, totaling 27,000 m2 of the experimental area. The indices performed well and were sensitive in class discrimination at intervals that range from soil exposure and stresses caused by pest and disease infestation (low vigor) to conditions in which the vegetation is in good development, in class intervals with high levels of vegetation and, consequently, pointing to high values of biomass. |
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Estimate of vigor classes of Brachiaria ruziziensis using sensors boarded on UAV plataform.Índice de vegetaçãoUAVForragemSensoriamento RemotoForageRemote sensingVegetation indexTraditional procedures for biomass estimation usually use destructive methods with great demands on time, resources, and labor. The development of models for automated estimation of pasture biomass, particularly from images captured by Unmanned Aerial Vehicle (UAV), in addition to high spatiotemporal resolution combined with flexibility in image acquisition, provides agility, the economy of resources, and labor. The objective of this work was to establish a technical feasibility study for the use of multispectral sensors onboard an Unmanned Aerial Vehicle (UAV) to estimate the vigor classes of Brachiaria ruziziensis pastures. For this purpose, imaging cameras in the visible (RGB), near-infrared and red edge ranges were used for continuous monitoring of 20 pasture paddocks with an area of 1,350 m2 each, totaling 27,000 m2 of the experimental area. The indices performed well and were sensitive in class discrimination at intervals that range from soil exposure and stresses caused by pest and disease infestation (low vigor) to conditions in which the vegetation is in good development, in class intervals with high levels of vegetation and, consequently, pointing to high values of biomass.RICARDO GUIMARAES ANDRADE, CNPGL; MARCOS CICARINI HOTT, CNPGL; WALTER COELHO P DE MAGALHAES JUNIOR, CNPGL; DOMINGOS SAVIO CAMPOS PACIULLO, CNPGL; CARLOS AUGUSTO DE MIRANDA GOMIDE, CNPGL.ANDRADE, R. G.HOTT, M. C.MAGALHAES JUNIOR, W. C. P. dePACIULLO, D. S. C.GOMIDE, C. A. de M.2021-12-29T02:02:03Z2021-12-29T02:02:03Z2021-12-282021info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleInternational Journal of Advanced Engineering Research and Science, v, 8, n. 12, p. 365-370, 2021.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1138479https://dx.doi.org/10.22161/ijaers.812.37enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2021-12-29T02:02:13Zoai:www.alice.cnptia.embrapa.br:doc/1138479Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542021-12-29T02:02:13falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542021-12-29T02:02:13Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Estimate of vigor classes of Brachiaria ruziziensis using sensors boarded on UAV plataform. |
title |
Estimate of vigor classes of Brachiaria ruziziensis using sensors boarded on UAV plataform. |
spellingShingle |
Estimate of vigor classes of Brachiaria ruziziensis using sensors boarded on UAV plataform. ANDRADE, R. G. Índice de vegetação UAV Forragem Sensoriamento Remoto Forage Remote sensing Vegetation index |
title_short |
Estimate of vigor classes of Brachiaria ruziziensis using sensors boarded on UAV plataform. |
title_full |
Estimate of vigor classes of Brachiaria ruziziensis using sensors boarded on UAV plataform. |
title_fullStr |
Estimate of vigor classes of Brachiaria ruziziensis using sensors boarded on UAV plataform. |
title_full_unstemmed |
Estimate of vigor classes of Brachiaria ruziziensis using sensors boarded on UAV plataform. |
title_sort |
Estimate of vigor classes of Brachiaria ruziziensis using sensors boarded on UAV plataform. |
author |
ANDRADE, R. G. |
author_facet |
ANDRADE, R. G. HOTT, M. C. MAGALHAES JUNIOR, W. C. P. de PACIULLO, D. S. C. GOMIDE, C. A. de M. |
author_role |
author |
author2 |
HOTT, M. C. MAGALHAES JUNIOR, W. C. P. de PACIULLO, D. S. C. GOMIDE, C. A. de M. |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
RICARDO GUIMARAES ANDRADE, CNPGL; MARCOS CICARINI HOTT, CNPGL; WALTER COELHO P DE MAGALHAES JUNIOR, CNPGL; DOMINGOS SAVIO CAMPOS PACIULLO, CNPGL; CARLOS AUGUSTO DE MIRANDA GOMIDE, CNPGL. |
dc.contributor.author.fl_str_mv |
ANDRADE, R. G. HOTT, M. C. MAGALHAES JUNIOR, W. C. P. de PACIULLO, D. S. C. GOMIDE, C. A. de M. |
dc.subject.por.fl_str_mv |
Índice de vegetação UAV Forragem Sensoriamento Remoto Forage Remote sensing Vegetation index |
topic |
Índice de vegetação UAV Forragem Sensoriamento Remoto Forage Remote sensing Vegetation index |
description |
Traditional procedures for biomass estimation usually use destructive methods with great demands on time, resources, and labor. The development of models for automated estimation of pasture biomass, particularly from images captured by Unmanned Aerial Vehicle (UAV), in addition to high spatiotemporal resolution combined with flexibility in image acquisition, provides agility, the economy of resources, and labor. The objective of this work was to establish a technical feasibility study for the use of multispectral sensors onboard an Unmanned Aerial Vehicle (UAV) to estimate the vigor classes of Brachiaria ruziziensis pastures. For this purpose, imaging cameras in the visible (RGB), near-infrared and red edge ranges were used for continuous monitoring of 20 pasture paddocks with an area of 1,350 m2 each, totaling 27,000 m2 of the experimental area. The indices performed well and were sensitive in class discrimination at intervals that range from soil exposure and stresses caused by pest and disease infestation (low vigor) to conditions in which the vegetation is in good development, in class intervals with high levels of vegetation and, consequently, pointing to high values of biomass. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-12-29T02:02:03Z 2021-12-29T02:02:03Z 2021-12-28 2021 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
International Journal of Advanced Engineering Research and Science, v, 8, n. 12, p. 365-370, 2021. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1138479 https://dx.doi.org/10.22161/ijaers.812.37 |
identifier_str_mv |
International Journal of Advanced Engineering Research and Science, v, 8, n. 12, p. 365-370, 2021. |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1138479 https://dx.doi.org/10.22161/ijaers.812.37 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
collection |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
repository.name.fl_str_mv |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
cg-riaa@embrapa.br |
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1794503515694956544 |