Identifying drought events in sugarcane using drought indices derived from Modis sensor

Detalhes bibliográficos
Autor(a) principal: Picoli, Michelle Cristina Araujo
Data de Publicação: 2017
Outros Autores: Duft, Daniel Garbellini, Machado, Pedro Gerber
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Pesquisa Agropecuária Brasileira (Online)
Texto Completo: https://seer.sct.embrapa.br/index.php/pab/article/view/24449
Resumo: The objective of this work was to evaluate the potential of several spectral indices, calculated using moderate resolution imaging spectroradiometer (Modis) images, in identifying drought events in sugarcane (Saccharum officinarum) crops. Images of Terra and Aqua satellites were used to calculate the spectral indices, using visible (red), near infrared, and shortwave infrared bands, and eight indices were selected: NDVI, EVI2, GVMI, NDI6, NDI7, NDWI, SRWI, and MSI. The indices were calculated using images between October and April of the crop years 2007/08, 2008/09, 2009/10, and 2013/14. These indices were then correlated with the standardized precipitation-evapotranspiration index (SPEI), calculated for 1, 3, and 6 months. Four of them had significant correlations with SPEI: GVMI, MSI, NDI7, and NDWI. Spectral indices from Modis sensor on board the Aqua satellite (MYD) were more suited for drought detection, and March provided the most relevant indices for that purpose. Drought indices calculated from Modis sensor data are effective for detecting sugarcane drought events, besides being able to indicate seasonal fluctuations.
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spelling Identifying drought events in sugarcane using drought indices derived from Modis sensorIdentificação de eventos de seca em cana-de-açúcar com base em índices de seca derivados do sensor ModisSaccharum officinarum; drought stress; image processing; satellite imagery; SPEI; warning systemsSaccharum officinarum; stress hídrico; processamento de imagens; imagem por satélite; SPEI; sistemas de alertaThe objective of this work was to evaluate the potential of several spectral indices, calculated using moderate resolution imaging spectroradiometer (Modis) images, in identifying drought events in sugarcane (Saccharum officinarum) crops. Images of Terra and Aqua satellites were used to calculate the spectral indices, using visible (red), near infrared, and shortwave infrared bands, and eight indices were selected: NDVI, EVI2, GVMI, NDI6, NDI7, NDWI, SRWI, and MSI. The indices were calculated using images between October and April of the crop years 2007/08, 2008/09, 2009/10, and 2013/14. These indices were then correlated with the standardized precipitation-evapotranspiration index (SPEI), calculated for 1, 3, and 6 months. Four of them had significant correlations with SPEI: GVMI, MSI, NDI7, and NDWI. Spectral indices from Modis sensor on board the Aqua satellite (MYD) were more suited for drought detection, and March provided the most relevant indices for that purpose. Drought indices calculated from Modis sensor data are effective for detecting sugarcane drought events, besides being able to indicate seasonal fluctuations.O objetivo deste trabalho foi avaliar o potencial de diversos índices, calculados com o uso de imagens do sensor Modis (“moderate resolution imaging spectroradiometer”), em identificar eventos de seca na cana-de-açúcar (Saccharum officinarum). As imagens dos satélites Terra e Aqua foram utilizadas para calcular os índices espectrais, com bandas na região do visível (vermelho), infravermelho próximo e infravermelho médio, e oito índices foram selecionados: NDVI, EVI2, GVMI, NDI6, NDI7, NDWI, SRWI e MSI. Os índices foram calculados com base em imagens de outubro a abril de quatro anos agrícolas: 2007/08, 2008/09, 2009/10 e 2013/14. Esses índices foram correlacionados com o índice de seca meteorológica SPEI, calculado para 1, 3 e 6 meses. Quatro deles tiveram correlação significativa com o índice SPEI: GVMI, MSI, NDI7 e NDWI. Os índices espectrais derivados do sensor Modis a bordo do satélite Aqua (MYD) são mais adequados para o reconhecimento de eventos de seca, e março proporcionou os índices mais relevantes para esse propósito. Índices de seca calculados com base em dados Modis são efetivos em detectar eventos de seca em cana-de-açúcar, além de serem capazes de apontar flutuações sazonais.Pesquisa Agropecuaria BrasileiraPesquisa Agropecuária BrasileiraFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), projeto 2014/17090-5Dr. Júlio Esquerdo, Embrapa-CNPTIADr. Guerric Le Maire, Centre de coopération internationale en recherche agronomique pour le développement (CIRAD)Picoli, Michelle Cristina AraujoDuft, Daniel GarbelliniMachado, Pedro Gerber2017-12-18info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.sct.embrapa.br/index.php/pab/article/view/24449Pesquisa Agropecuaria Brasileira; v.52, n.11, nov. 2017; 1063-1071Pesquisa Agropecuária Brasileira; v.52, n.11, nov. 2017; 1063-10711678-39210100-104xreponame:Pesquisa Agropecuária Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAenghttps://seer.sct.embrapa.br/index.php/pab/article/view/24449/14023https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/24449/16294Direitos autorais 2017 Pesquisa Agropecuária Brasileirainfo:eu-repo/semantics/openAccess2018-01-04T11:40:52Zoai:ojs.seer.sct.embrapa.br:article/24449Revistahttp://seer.sct.embrapa.br/index.php/pabPRIhttps://old.scielo.br/oai/scielo-oai.phppab@sct.embrapa.br || sct.pab@embrapa.br1678-39210100-204Xopendoar:2018-01-04T11:40:52Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Identifying drought events in sugarcane using drought indices derived from Modis sensor
Identificação de eventos de seca em cana-de-açúcar com base em índices de seca derivados do sensor Modis
title Identifying drought events in sugarcane using drought indices derived from Modis sensor
spellingShingle Identifying drought events in sugarcane using drought indices derived from Modis sensor
Picoli, Michelle Cristina Araujo
Saccharum officinarum; drought stress; image processing; satellite imagery; SPEI; warning systems
Saccharum officinarum; stress hídrico; processamento de imagens; imagem por satélite; SPEI; sistemas de alerta
title_short Identifying drought events in sugarcane using drought indices derived from Modis sensor
title_full Identifying drought events in sugarcane using drought indices derived from Modis sensor
title_fullStr Identifying drought events in sugarcane using drought indices derived from Modis sensor
title_full_unstemmed Identifying drought events in sugarcane using drought indices derived from Modis sensor
title_sort Identifying drought events in sugarcane using drought indices derived from Modis sensor
author Picoli, Michelle Cristina Araujo
author_facet Picoli, Michelle Cristina Araujo
Duft, Daniel Garbellini
Machado, Pedro Gerber
author_role author
author2 Duft, Daniel Garbellini
Machado, Pedro Gerber
author2_role author
author
dc.contributor.none.fl_str_mv Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), projeto 2014/17090-5
Dr. Júlio Esquerdo, Embrapa-CNPTIA
Dr. Guerric Le Maire, Centre de coopération internationale en recherche agronomique pour le développement (CIRAD)
dc.contributor.author.fl_str_mv Picoli, Michelle Cristina Araujo
Duft, Daniel Garbellini
Machado, Pedro Gerber
dc.subject.por.fl_str_mv Saccharum officinarum; drought stress; image processing; satellite imagery; SPEI; warning systems
Saccharum officinarum; stress hídrico; processamento de imagens; imagem por satélite; SPEI; sistemas de alerta
topic Saccharum officinarum; drought stress; image processing; satellite imagery; SPEI; warning systems
Saccharum officinarum; stress hídrico; processamento de imagens; imagem por satélite; SPEI; sistemas de alerta
description The objective of this work was to evaluate the potential of several spectral indices, calculated using moderate resolution imaging spectroradiometer (Modis) images, in identifying drought events in sugarcane (Saccharum officinarum) crops. Images of Terra and Aqua satellites were used to calculate the spectral indices, using visible (red), near infrared, and shortwave infrared bands, and eight indices were selected: NDVI, EVI2, GVMI, NDI6, NDI7, NDWI, SRWI, and MSI. The indices were calculated using images between October and April of the crop years 2007/08, 2008/09, 2009/10, and 2013/14. These indices were then correlated with the standardized precipitation-evapotranspiration index (SPEI), calculated for 1, 3, and 6 months. Four of them had significant correlations with SPEI: GVMI, MSI, NDI7, and NDWI. Spectral indices from Modis sensor on board the Aqua satellite (MYD) were more suited for drought detection, and March provided the most relevant indices for that purpose. Drought indices calculated from Modis sensor data are effective for detecting sugarcane drought events, besides being able to indicate seasonal fluctuations.
publishDate 2017
dc.date.none.fl_str_mv 2017-12-18
dc.type.none.fl_str_mv
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://seer.sct.embrapa.br/index.php/pab/article/view/24449
url https://seer.sct.embrapa.br/index.php/pab/article/view/24449
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://seer.sct.embrapa.br/index.php/pab/article/view/24449/14023
https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/24449/16294
dc.rights.driver.fl_str_mv Direitos autorais 2017 Pesquisa Agropecuária Brasileira
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Direitos autorais 2017 Pesquisa Agropecuária Brasileira
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Pesquisa Agropecuaria Brasileira
Pesquisa Agropecuária Brasileira
publisher.none.fl_str_mv Pesquisa Agropecuaria Brasileira
Pesquisa Agropecuária Brasileira
dc.source.none.fl_str_mv Pesquisa Agropecuaria Brasileira; v.52, n.11, nov. 2017; 1063-1071
Pesquisa Agropecuária Brasileira; v.52, n.11, nov. 2017; 1063-1071
1678-3921
0100-104x
reponame:Pesquisa Agropecuária Brasileira (Online)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Pesquisa Agropecuária Brasileira (Online)
collection Pesquisa Agropecuária Brasileira (Online)
repository.name.fl_str_mv Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv pab@sct.embrapa.br || sct.pab@embrapa.br
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