RGB vegetation indices applied to grass monitoring: a qualitative analysis
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/40314 |
Resumo: | In developing countries such as Brazil, research on low-cost remote sensing and computational techniques become essential for the development of precision agriculture (PA), and improving the quality of the agricultural products. Faced with the scenario of increasing production of emerald grass (Zoysia Japônica) in Brazil, and the value added the quality of this agricultural product. The objective of this work was to evaluate the performance of RGB (IV) vegetation indices in the identification of exposed soil and vegetation. The study was developed in an irrigated area of 58 ha cultivated with emerald grass at Bom Sucesso, Minas Gerais, Brazil. The images were obtained by a RGB digital camera coupled to an remotely piloted aircraft. The flight plan was setup to take overlapping images of 70% and the aircraft speed was 10 m s -1 . Six RGB Vegetation index (MGVRI, GLI, RGBVI, MPRI, VEG, ExG) were evaluated in a mosaic resulting from the images of the study area. All of the VIs evaluated were affected by the variability of lighting conditions in the area but MPRI and MGVRI were the ones that presented the best results in a qualitative evaluation regarding the discrimination of vegetation and soil. |
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RGB vegetation indices applied to grass monitoring: a qualitative analysisEmerald grassIndex vegetation RGBPrecision agricultureAgricultural products - ImprovementGrama esmeraldaÍndice de vegetação RGBAgricultura de precisãoProdutos agrícolas - MelhoramentoIn developing countries such as Brazil, research on low-cost remote sensing and computational techniques become essential for the development of precision agriculture (PA), and improving the quality of the agricultural products. Faced with the scenario of increasing production of emerald grass (Zoysia Japônica) in Brazil, and the value added the quality of this agricultural product. The objective of this work was to evaluate the performance of RGB (IV) vegetation indices in the identification of exposed soil and vegetation. The study was developed in an irrigated area of 58 ha cultivated with emerald grass at Bom Sucesso, Minas Gerais, Brazil. The images were obtained by a RGB digital camera coupled to an remotely piloted aircraft. The flight plan was setup to take overlapping images of 70% and the aircraft speed was 10 m s -1 . Six RGB Vegetation index (MGVRI, GLI, RGBVI, MPRI, VEG, ExG) were evaluated in a mosaic resulting from the images of the study area. All of the VIs evaluated were affected by the variability of lighting conditions in the area but MPRI and MGVRI were the ones that presented the best results in a qualitative evaluation regarding the discrimination of vegetation and soil.Estonian University of Life Sciences2020-04-24T13:10:54Z2020-04-24T13:10:54Z2019info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfBARBOSA, B. D. S. et al. RGB vegetation indices applied to grass monitoring: a qualitative analysis. Agronomy Research, Tarfu, v. 17, n. 2, p. 349-357, 2019.http://repositorio.ufla.br/jspui/handle/1/40314Agronomy Researchreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessBarbosa, B. D. S.Ferraz, G. A. S.Gonçalves, L. M.Marin, D. B.Maciel, D. T.Ferraz, P. F. P.Rossi, G.eng2020-04-24T13:10:55Zoai:localhost:1/40314Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2020-04-24T13:10:55Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
RGB vegetation indices applied to grass monitoring: a qualitative analysis |
title |
RGB vegetation indices applied to grass monitoring: a qualitative analysis |
spellingShingle |
RGB vegetation indices applied to grass monitoring: a qualitative analysis Barbosa, B. D. S. Emerald grass Index vegetation RGB Precision agriculture Agricultural products - Improvement Grama esmeralda Índice de vegetação RGB Agricultura de precisão Produtos agrícolas - Melhoramento |
title_short |
RGB vegetation indices applied to grass monitoring: a qualitative analysis |
title_full |
RGB vegetation indices applied to grass monitoring: a qualitative analysis |
title_fullStr |
RGB vegetation indices applied to grass monitoring: a qualitative analysis |
title_full_unstemmed |
RGB vegetation indices applied to grass monitoring: a qualitative analysis |
title_sort |
RGB vegetation indices applied to grass monitoring: a qualitative analysis |
author |
Barbosa, B. D. S. |
author_facet |
Barbosa, B. D. S. Ferraz, G. A. S. Gonçalves, L. M. Marin, D. B. Maciel, D. T. Ferraz, P. F. P. Rossi, G. |
author_role |
author |
author2 |
Ferraz, G. A. S. Gonçalves, L. M. Marin, D. B. Maciel, D. T. Ferraz, P. F. P. Rossi, G. |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Barbosa, B. D. S. Ferraz, G. A. S. Gonçalves, L. M. Marin, D. B. Maciel, D. T. Ferraz, P. F. P. Rossi, G. |
dc.subject.por.fl_str_mv |
Emerald grass Index vegetation RGB Precision agriculture Agricultural products - Improvement Grama esmeralda Índice de vegetação RGB Agricultura de precisão Produtos agrícolas - Melhoramento |
topic |
Emerald grass Index vegetation RGB Precision agriculture Agricultural products - Improvement Grama esmeralda Índice de vegetação RGB Agricultura de precisão Produtos agrícolas - Melhoramento |
description |
In developing countries such as Brazil, research on low-cost remote sensing and computational techniques become essential for the development of precision agriculture (PA), and improving the quality of the agricultural products. Faced with the scenario of increasing production of emerald grass (Zoysia Japônica) in Brazil, and the value added the quality of this agricultural product. The objective of this work was to evaluate the performance of RGB (IV) vegetation indices in the identification of exposed soil and vegetation. The study was developed in an irrigated area of 58 ha cultivated with emerald grass at Bom Sucesso, Minas Gerais, Brazil. The images were obtained by a RGB digital camera coupled to an remotely piloted aircraft. The flight plan was setup to take overlapping images of 70% and the aircraft speed was 10 m s -1 . Six RGB Vegetation index (MGVRI, GLI, RGBVI, MPRI, VEG, ExG) were evaluated in a mosaic resulting from the images of the study area. All of the VIs evaluated were affected by the variability of lighting conditions in the area but MPRI and MGVRI were the ones that presented the best results in a qualitative evaluation regarding the discrimination of vegetation and soil. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019 2020-04-24T13:10:54Z 2020-04-24T13:10:54Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
BARBOSA, B. D. S. et al. RGB vegetation indices applied to grass monitoring: a qualitative analysis. Agronomy Research, Tarfu, v. 17, n. 2, p. 349-357, 2019. http://repositorio.ufla.br/jspui/handle/1/40314 |
identifier_str_mv |
BARBOSA, B. D. S. et al. RGB vegetation indices applied to grass monitoring: a qualitative analysis. Agronomy Research, Tarfu, v. 17, n. 2, p. 349-357, 2019. |
url |
http://repositorio.ufla.br/jspui/handle/1/40314 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Estonian University of Life Sciences |
publisher.none.fl_str_mv |
Estonian University of Life Sciences |
dc.source.none.fl_str_mv |
Agronomy Research reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
_version_ |
1784549983750455296 |