Crop parameters and spectral response of coffee (Coffea arabica L.) areas within the State of Minas Gerais, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2007 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng por spa |
Título da fonte: | Coffee Science (Online) |
Texto Completo: | https://coffeescience.ufla.br/index.php/Coffeescience/article/view/26 |
Resumo: | This work compares coffee plantation (Coffea arabica L.) characteristics to their spectral responses in TM/ Landsat images to obtain identification patterns to be used in mapping and monitoring of coffee crops in the state of Minas Gerais using remote sensing. The fieldwork involved selection of representative areas from the main coffee production regions of the state, with definition of study areas from where the coffee parameters and environmental data were collected. Two pilot-areas representative of the physiographic regions, Alto Paranaíba and Sul de Minas were selected for the study. The field data and TM/Landsat images were treated with the SPRING geographic information system. The reflectance data, as well as the remaining data collected in the field, were organized in a statistical programme for correlation studies. The statistical analysis showed that, among the fourteen variables evaluated, the highest correlation was observed between reflectance measured in the near infrared zone and the percentage of area covered by the plant canopies. This parameter reflects the effects of other crop variables, such as size, diameter, density, vegetative vigour and productivity. Results show that, due to the great variability of the crop and the limitations imposed by TM/Landsat products, the definition of a pattern is unlikely. Nevertheless, for productive adult coffee plants in good vegetative state, the survey and monitoring of the crop can be carried out using TM/Landsat images, particularly in regions like Alto Paranaíba , where the landscape is mostly of gently undulating slopes and the coffee fields are more extensive and homogeneous. |
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Crop parameters and spectral response of coffee (Coffea arabica L.) areas within the State of Minas Gerais, BrazilParâmetros culturais para avaliação do comportamento espectral da cultura do café (Coffea arabica L.) em Minas Gerais, BrasilSensoriamento remotoSIGimagens Landsatuso da terramapeamentoThis work compares coffee plantation (Coffea arabica L.) characteristics to their spectral responses in TM/ Landsat images to obtain identification patterns to be used in mapping and monitoring of coffee crops in the state of Minas Gerais using remote sensing. The fieldwork involved selection of representative areas from the main coffee production regions of the state, with definition of study areas from where the coffee parameters and environmental data were collected. Two pilot-areas representative of the physiographic regions, Alto Paranaíba and Sul de Minas were selected for the study. The field data and TM/Landsat images were treated with the SPRING geographic information system. The reflectance data, as well as the remaining data collected in the field, were organized in a statistical programme for correlation studies. The statistical analysis showed that, among the fourteen variables evaluated, the highest correlation was observed between reflectance measured in the near infrared zone and the percentage of area covered by the plant canopies. This parameter reflects the effects of other crop variables, such as size, diameter, density, vegetative vigour and productivity. Results show that, due to the great variability of the crop and the limitations imposed by TM/Landsat products, the definition of a pattern is unlikely. Nevertheless, for productive adult coffee plants in good vegetative state, the survey and monitoring of the crop can be carried out using TM/Landsat images, particularly in regions like Alto Paranaíba , where the landscape is mostly of gently undulating slopes and the coffee fields are more extensive and homogeneous.Neste trabalho foi avaliada a correlação entre parâmetros culturais e respostas espectrais da cultura cafeeira (Coffea arabica L) em imagens TM/Landsat, para estabelecer padrões de identificação desta cultura por sensoriamento remoto, a serem utilizados no zoneamento e monitoramento do parque cafeeiro de Minas Gerais. Para estudo foi selecionada uma área piloto em Patrocínio, região do Alto Paranaíba, e outra em Machado, região Sul de Minas. O Sistema de Informação Geográfica SPRING foi utilizado para tratamento dos dados e criação de um banco de dados geográfico. As respostas espectrais foram avaliadas pelas reflectâncias médias, estimadas a partir dos valores de pixels de imagens TM/Landsat, para cada um dos talhões geo-referenciados em campo. Dentre as quatorze variáveis avaliadas, a melhor correlação foi observada entre a reflectância medida na zona do infravermelho próximo e a porcentagem da área coberta pelas plantas. Este parâmetro reflete outras variáveis culturais do café, tais como porte, diâmetro, densidade, vigor vegetativo e produção média. A cultura cafeeira apresenta uma resposta espectral complexa. Em função da grande variabilidade das lavouras de café e da resolução espacial das imagens TM/Landsat, a definição de um padrão de identificação para a cultura foi dificultada. Contudo, imagens TM/Landsat podem ser usadas no levantamento e monitoramento de áreas cafeeiras, particularmente nos casos de cafezais em produção e em bom estado vegetativo de regiões como Patrocínio, onde o relevo é suave a suave ondulado e as lavouras ocupam grandes extensões e são mais homogêneas.Editora UFLA2007-12-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfapplication/pdfhttps://coffeescience.ufla.br/index.php/Coffeescience/article/view/26Coffee Science - ISSN 1984-3909; Vol. 1 No. 2 (2006); p. 111-118Coffee Science; Vol. 1 Núm. 2 (2006); p. 111-118Coffee Science; v. 1 n. 2 (2006); p. 111-1181984-3909reponame:Coffee Science (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAengporspahttps://coffeescience.ufla.br/index.php/Coffeescience/article/view/26/22https://coffeescience.ufla.br/index.php/Coffeescience/article/view/26/98https://coffeescience.ufla.br/index.php/Coffeescience/article/view/26/99Copyright (c) 2007 Coffee Science - ISSN 1984-3909https://creativecommons.org/info:eu-repo/semantics/openAccessVieira, Tatiana Grossi ChquiloffAlves, Helena Maria RamosLacerda, Marilusa Pinto CoelhoVeiga, Ruben DellyEpiphanio, José Carlos Neves2013-02-23T12:24:23Zoai:coffeescience.ufla.br:article/26Revistahttps://coffeescience.ufla.br/index.php/CoffeesciencePUBhttps://coffeescience.ufla.br/index.php/Coffeescience/oaicoffeescience@dag.ufla.br||coffeescience@dag.ufla.br|| alvaro-cozadi@hotmail.com1984-39091809-6875opendoar:2024-05-21T19:53:26.557943Coffee Science (Online) - Universidade Federal de Lavras (UFLA)true |
dc.title.none.fl_str_mv |
Crop parameters and spectral response of coffee (Coffea arabica L.) areas within the State of Minas Gerais, Brazil Parâmetros culturais para avaliação do comportamento espectral da cultura do café (Coffea arabica L.) em Minas Gerais, Brasil |
title |
Crop parameters and spectral response of coffee (Coffea arabica L.) areas within the State of Minas Gerais, Brazil |
spellingShingle |
Crop parameters and spectral response of coffee (Coffea arabica L.) areas within the State of Minas Gerais, Brazil Vieira, Tatiana Grossi Chquiloff Sensoriamento remoto SIG imagens Landsat uso da terra mapeamento |
title_short |
Crop parameters and spectral response of coffee (Coffea arabica L.) areas within the State of Minas Gerais, Brazil |
title_full |
Crop parameters and spectral response of coffee (Coffea arabica L.) areas within the State of Minas Gerais, Brazil |
title_fullStr |
Crop parameters and spectral response of coffee (Coffea arabica L.) areas within the State of Minas Gerais, Brazil |
title_full_unstemmed |
Crop parameters and spectral response of coffee (Coffea arabica L.) areas within the State of Minas Gerais, Brazil |
title_sort |
Crop parameters and spectral response of coffee (Coffea arabica L.) areas within the State of Minas Gerais, Brazil |
author |
Vieira, Tatiana Grossi Chquiloff |
author_facet |
Vieira, Tatiana Grossi Chquiloff Alves, Helena Maria Ramos Lacerda, Marilusa Pinto Coelho Veiga, Ruben Delly Epiphanio, José Carlos Neves |
author_role |
author |
author2 |
Alves, Helena Maria Ramos Lacerda, Marilusa Pinto Coelho Veiga, Ruben Delly Epiphanio, José Carlos Neves |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Vieira, Tatiana Grossi Chquiloff Alves, Helena Maria Ramos Lacerda, Marilusa Pinto Coelho Veiga, Ruben Delly Epiphanio, José Carlos Neves |
dc.subject.por.fl_str_mv |
Sensoriamento remoto SIG imagens Landsat uso da terra mapeamento |
topic |
Sensoriamento remoto SIG imagens Landsat uso da terra mapeamento |
description |
This work compares coffee plantation (Coffea arabica L.) characteristics to their spectral responses in TM/ Landsat images to obtain identification patterns to be used in mapping and monitoring of coffee crops in the state of Minas Gerais using remote sensing. The fieldwork involved selection of representative areas from the main coffee production regions of the state, with definition of study areas from where the coffee parameters and environmental data were collected. Two pilot-areas representative of the physiographic regions, Alto Paranaíba and Sul de Minas were selected for the study. The field data and TM/Landsat images were treated with the SPRING geographic information system. The reflectance data, as well as the remaining data collected in the field, were organized in a statistical programme for correlation studies. The statistical analysis showed that, among the fourteen variables evaluated, the highest correlation was observed between reflectance measured in the near infrared zone and the percentage of area covered by the plant canopies. This parameter reflects the effects of other crop variables, such as size, diameter, density, vegetative vigour and productivity. Results show that, due to the great variability of the crop and the limitations imposed by TM/Landsat products, the definition of a pattern is unlikely. Nevertheless, for productive adult coffee plants in good vegetative state, the survey and monitoring of the crop can be carried out using TM/Landsat images, particularly in regions like Alto Paranaíba , where the landscape is mostly of gently undulating slopes and the coffee fields are more extensive and homogeneous. |
publishDate |
2007 |
dc.date.none.fl_str_mv |
2007-12-14 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/26 |
url |
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/26 |
dc.language.iso.fl_str_mv |
eng por spa |
language |
eng por spa |
dc.relation.none.fl_str_mv |
https://coffeescience.ufla.br/index.php/Coffeescience/article/view/26/22 https://coffeescience.ufla.br/index.php/Coffeescience/article/view/26/98 https://coffeescience.ufla.br/index.php/Coffeescience/article/view/26/99 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2007 Coffee Science - ISSN 1984-3909 https://creativecommons.org/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2007 Coffee Science - ISSN 1984-3909 https://creativecommons.org/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Editora UFLA |
publisher.none.fl_str_mv |
Editora UFLA |
dc.source.none.fl_str_mv |
Coffee Science - ISSN 1984-3909; Vol. 1 No. 2 (2006); p. 111-118 Coffee Science; Vol. 1 Núm. 2 (2006); p. 111-118 Coffee Science; v. 1 n. 2 (2006); p. 111-118 1984-3909 reponame:Coffee Science (Online) instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Coffee Science (Online) |
collection |
Coffee Science (Online) |
repository.name.fl_str_mv |
Coffee Science (Online) - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
coffeescience@dag.ufla.br||coffeescience@dag.ufla.br|| alvaro-cozadi@hotmail.com |
_version_ |
1799874918244941824 |