Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI)
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Pesquisa Agropecuária Tropical (Online) |
Texto Completo: | https://revistas.ufg.br/pat/article/view/39303 |
Resumo: | Large farmland areas and the knowledge on the interaction between solar radiation and vegetation canopies have increased the use of data from orbital remote sensors in sugarcane monitoring. However, the constituents of the atmosphere affect the reflectance values obtained by imaging sensors. This study aimed at improving a sugarcane Leaf Area Index (LAI) estimation model, concerning the Normalized Difference Vegetation Index (NDVI) subjected to atmospheric correction. The model generated by the NDVI with atmospheric correction showed the best results (R² = 0.84; d = 0.95; MAE = 0.44; RMSE = 0.55), in relation to the other models compared. LAI estimation with this model, during the sugarcane plant cycle, reached a maximum of 4.8 at the vegetative growth phase and 2.3 at the end of the maturation phase. Thus, the use of atmospheric correction to estimate the sugarcane LAI is recommended, since this procedure increases the correlations between the LAI estimated by image and by plant parameters. |
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Pesquisa Agropecuária Tropical (Online) |
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Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI)Estimativa da área foliar de cana-de-açúcar a partir do índice de vegetação por diferença normalizada (NDVI) corrigidoSaccharum spp.vegetal growthimage analysis.Saccharum spp.crescimento vegetalprocessamento de imagem.Large farmland areas and the knowledge on the interaction between solar radiation and vegetation canopies have increased the use of data from orbital remote sensors in sugarcane monitoring. However, the constituents of the atmosphere affect the reflectance values obtained by imaging sensors. This study aimed at improving a sugarcane Leaf Area Index (LAI) estimation model, concerning the Normalized Difference Vegetation Index (NDVI) subjected to atmospheric correction. The model generated by the NDVI with atmospheric correction showed the best results (R² = 0.84; d = 0.95; MAE = 0.44; RMSE = 0.55), in relation to the other models compared. LAI estimation with this model, during the sugarcane plant cycle, reached a maximum of 4.8 at the vegetative growth phase and 2.3 at the end of the maturation phase. Thus, the use of atmospheric correction to estimate the sugarcane LAI is recommended, since this procedure increases the correlations between the LAI estimated by image and by plant parameters.As grandes extensões de terras cultivadas e o entendimento da interação da radiação solar com os dosséis vegetativos têm viabilizado a utilização dos dados de sensores remotos orbitais no monitoramento da cana-de-açúcar. Entretanto, os efeitos atenuantes atmosféricos interferem nos dados de refletância obtidos pelo sensoriamento remoto óptico. Objetivou-se calibrar um modelo de estimativa do Índice de Área Foliar (IAF) da cana-de-açúcar, em função do índice de vegetação por diferença normalizada (NDVI) submetido a correção atmosférica. O modelo gerado pelo NDVI corrigido apresentou os melhores resultados (R² = 0,84; d = 0,95; MAE = 0,44; RMSE = 0,55), em relação aos modelos comparados. A estimativa do IAF com esse modelo, durante o ciclo de cana-planta, obteve um máximo de 4,8 na fase de crescimento vegetativo e 2,3 ao final da maturação. Assim, recomenda-se a aplicação de correção atmosférica para a estimativa do IAF da cana-de-açúcar, uma vez que tal procedimento aproxima o IAF estimado por imagem daquele estimado por parâmetros da planta.Escola de Agronomia - Universidade Federal de Goiás2016-06-21info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAvaliado por paresapplication/pdfhttps://revistas.ufg.br/pat/article/view/39303Pesquisa Agropecuária Tropical [Agricultural Research in the Tropics]; v. 46, n. 2, Apr./Jun. 2016; 140-148Pesquisa Agropecuária Tropical (Agricultural Research in the Tropics); v. 46, n. 2, abr./jun. 2016; 140-148Pesquisa Agropecuária Tropical; v. 46, n. 2, abr./jun. 2016; 140-1481983-4063reponame:Pesquisa Agropecuária Tropical (Online)instname:Universidade Federal de Goiás (UFG)instacron:UFGenghttps://revistas.ufg.br/pat/article/view/39303/21157Pereira, Rodrigo MouraCasaroli, DerblaiVellame, Lucas MeloAlves Júnior, JoséEvangelista, Adão Wagner Pêgoinfo:eu-repo/semantics/openAccess2020-07-13T17:56:28Zoai:ojs.revistas.ufg.br:article/39303Revistahttps://revistas.ufg.br/patPUBhttps://revistas.ufg.br/pat/oaiaseleguini.pat@gmail.com||mgoes@agro.ufg.br1983-40631517-6398opendoar:2024-05-21T19:56:11.532911Pesquisa Agropecuária Tropical (Online) - Universidade Federal de Goiás (UFG)true |
dc.title.none.fl_str_mv |
Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI) Estimativa da área foliar de cana-de-açúcar a partir do índice de vegetação por diferença normalizada (NDVI) corrigido |
title |
Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI) |
spellingShingle |
Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI) Pereira, Rodrigo Moura Saccharum spp. vegetal growth image analysis. Saccharum spp. crescimento vegetal processamento de imagem. |
title_short |
Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI) |
title_full |
Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI) |
title_fullStr |
Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI) |
title_full_unstemmed |
Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI) |
title_sort |
Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI) |
author |
Pereira, Rodrigo Moura |
author_facet |
Pereira, Rodrigo Moura Casaroli, Derblai Vellame, Lucas Melo Alves Júnior, José Evangelista, Adão Wagner Pêgo |
author_role |
author |
author2 |
Casaroli, Derblai Vellame, Lucas Melo Alves Júnior, José Evangelista, Adão Wagner Pêgo |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Pereira, Rodrigo Moura Casaroli, Derblai Vellame, Lucas Melo Alves Júnior, José Evangelista, Adão Wagner Pêgo |
dc.subject.por.fl_str_mv |
Saccharum spp. vegetal growth image analysis. Saccharum spp. crescimento vegetal processamento de imagem. |
topic |
Saccharum spp. vegetal growth image analysis. Saccharum spp. crescimento vegetal processamento de imagem. |
description |
Large farmland areas and the knowledge on the interaction between solar radiation and vegetation canopies have increased the use of data from orbital remote sensors in sugarcane monitoring. However, the constituents of the atmosphere affect the reflectance values obtained by imaging sensors. This study aimed at improving a sugarcane Leaf Area Index (LAI) estimation model, concerning the Normalized Difference Vegetation Index (NDVI) subjected to atmospheric correction. The model generated by the NDVI with atmospheric correction showed the best results (R² = 0.84; d = 0.95; MAE = 0.44; RMSE = 0.55), in relation to the other models compared. LAI estimation with this model, during the sugarcane plant cycle, reached a maximum of 4.8 at the vegetative growth phase and 2.3 at the end of the maturation phase. Thus, the use of atmospheric correction to estimate the sugarcane LAI is recommended, since this procedure increases the correlations between the LAI estimated by image and by plant parameters. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-06-21 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Avaliado por pares |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://revistas.ufg.br/pat/article/view/39303 |
url |
https://revistas.ufg.br/pat/article/view/39303 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://revistas.ufg.br/pat/article/view/39303/21157 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Escola de Agronomia - Universidade Federal de Goiás |
publisher.none.fl_str_mv |
Escola de Agronomia - Universidade Federal de Goiás |
dc.source.none.fl_str_mv |
Pesquisa Agropecuária Tropical [Agricultural Research in the Tropics]; v. 46, n. 2, Apr./Jun. 2016; 140-148 Pesquisa Agropecuária Tropical (Agricultural Research in the Tropics); v. 46, n. 2, abr./jun. 2016; 140-148 Pesquisa Agropecuária Tropical; v. 46, n. 2, abr./jun. 2016; 140-148 1983-4063 reponame:Pesquisa Agropecuária Tropical (Online) instname:Universidade Federal de Goiás (UFG) instacron:UFG |
instname_str |
Universidade Federal de Goiás (UFG) |
instacron_str |
UFG |
institution |
UFG |
reponame_str |
Pesquisa Agropecuária Tropical (Online) |
collection |
Pesquisa Agropecuária Tropical (Online) |
repository.name.fl_str_mv |
Pesquisa Agropecuária Tropical (Online) - Universidade Federal de Goiás (UFG) |
repository.mail.fl_str_mv |
aseleguini.pat@gmail.com||mgoes@agro.ufg.br |
_version_ |
1799874819323330560 |