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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
10/08/2009 |
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Data da última atualização: |
15/01/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso / Nota Técnica |
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Autoria: |
NASCIMENTO, C. R.; ZULLO JÚNIOR, J.; ROMANI, L. A. S.; RODRIGUES, L. H. A. |
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Afiliação: |
C. R. NASCIMENTO, FEAGRI/UNICAMP; J. ZULLO JÚNIOR, CEPAGRI/UNICAMP; LUCIANA ALVIM SANTOS ROMANI, CNPTIA; L. H. A. RODRIGUES, FEAGRI/UNICAMP. |
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Título: |
Identification of sugar cane fields in the state of sao paulo using a time series of AVHRR/NOAA satellite images. |
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Ano de publicação: |
2009 |
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Fonte/Imprenta: |
In: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTI-TEMPORAL REMOTE SENSING IMAGES, 5., 2009, Groton, Connecticut. Proceedings... Storrs: UConn, 2009. |
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Páginas: |
p. 104-111. |
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Idioma: |
Inglês |
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Notas: |
MultiTemp 2009. |
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Conteúdo: |
Brazil is the first world producer of sugar cane. Despite the economic and social importance of agribusiness to Brazil, it is still difficult to estimate the harvest of the its main agricultural crops with the precision and anticipation needed, justifying the study and development of new methods based on the use of remote sensing data, for example. Even considering the increasing availability of high spatial resolution images in recent years, AVHRR/NOAA satellites have some characteristics suitable for application in operational methods of agricultural monitoring specially for a crop like sugar cane. Thus, this paper had the main objective to identify sugar cane areas in the state of Sao Paulo using harmonic analysis applied to a time series of AVHRR/NOAA-17 available at CEPAGRI/UNICAMP. A decision tree was calculated to search patterns that could represent the sugar cane along the crop season 2006/2007. Application of these two methods (harmonic analysis and decision tree) on the time series used was able to identify sugar cane areas in the state of Sao Paulo (Brazil) with 92% confidence when compared to ground truth based on LANDSAT/TM images and available at CANASAT?s webpage (http://www.dsr.inpe.br/canasat). This methodology can be applied in an operational way to support the official systems of harvest forecasting. |
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Palavras-Chave: |
Análise harmônica; Árvore de decisão; Georreferenciamento; Processamento de imagens NDVI; Séries temporais de AVHRR/NOAA-17. |
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Thesagro: |
Agricultura; Cana de açúcar; Sensoriamento remoto. |
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Thesaurus Nal: |
Image analysis; Remote sensing; Sugarcane. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02387nam a2200301 a 4500
001 1256611
005 2020-01-15
008 2009 bl uuuu u00u1 u #d
100 1 $aNASCIMENTO, C. R.
245 $aIdentification of sugar cane fields in the state of sao paulo using a time series of AVHRR/NOAA satellite images.$h[electronic resource]
260 $aIn: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTI-TEMPORAL REMOTE SENSING IMAGES, 5., 2009, Groton, Connecticut. Proceedings... Storrs: UConn$c2009
300 $ap. 104-111.
500 $aMultiTemp 2009.
520 $aBrazil is the first world producer of sugar cane. Despite the economic and social importance of agribusiness to Brazil, it is still difficult to estimate the harvest of the its main agricultural crops with the precision and anticipation needed, justifying the study and development of new methods based on the use of remote sensing data, for example. Even considering the increasing availability of high spatial resolution images in recent years, AVHRR/NOAA satellites have some characteristics suitable for application in operational methods of agricultural monitoring specially for a crop like sugar cane. Thus, this paper had the main objective to identify sugar cane areas in the state of Sao Paulo using harmonic analysis applied to a time series of AVHRR/NOAA-17 available at CEPAGRI/UNICAMP. A decision tree was calculated to search patterns that could represent the sugar cane along the crop season 2006/2007. Application of these two methods (harmonic analysis and decision tree) on the time series used was able to identify sugar cane areas in the state of Sao Paulo (Brazil) with 92% confidence when compared to ground truth based on LANDSAT/TM images and available at CANASAT?s webpage (http://www.dsr.inpe.br/canasat). This methodology can be applied in an operational way to support the official systems of harvest forecasting.
650 $aImage analysis
650 $aRemote sensing
650 $aSugarcane
650 $aAgricultura
650 $aCana de açúcar
650 $aSensoriamento remoto
653 $aAnálise harmônica
653 $aÁrvore de decisão
653 $aGeorreferenciamento
653 $aProcessamento de imagens NDVI
653 $aSéries temporais de AVHRR/NOAA-17
700 1 $aZULLO JÚNIOR, J.
700 1 $aROMANI, L. A. S.
700 1 $aRODRIGUES, L. H. A.
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Embrapa Agricultura Digital (CNPTIA) |
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| 2. |  | MIGUEL, E. P.; REZENDE, A. V.; LEAL, F. A.; MATRICARDI, E. A. T.; VALE, A. T. do; PEREIRA, R. S. Redes neurais artificiais para a modelagem do volume de madeira e biomassa do cerradão com dados de satélites. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 50, n. 9, p. 829-839, set. 2015. Título em inglês: Artificial neural networks for modeling wood volume and aboveground biomass of tall Cerrado using satellite data.| Biblioteca(s): Embrapa Unidades Centrais. |
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