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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: |
ROMANI, L. A. S.; ZULLO JÚNIOR, J.; NASCIMENTO, C. R.; GONÇALVES, R. R. V.; TRAINA, C; TRAINA, A. J. M. |
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Afiliação: |
LUCIANA ALVIM SANTOS ROMANI, CNPTIA; JURANDIR ZULLO JÚNIOR, CEPAGRI/UNICAMP; C. R. NASCIMENTO, FEAGRI/UNICAMP; R. R. V. GONÇALVES, FEAGRI/UNICAMP; C. TRAINA, ICMC/USP; A. J. M. TRAINA, ICMC/USP. |
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Título: |
Monitoring sugar cane crops through DTW-based method for similarity search in NDVI time series. |
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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. 171-178. |
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Idioma: |
Inglês |
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Notas: |
MultiTemp 2009. |
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Conteúdo: |
Brazil is an important sugar cane producer, which is the main resource for ethanol production, a renewable source of energy. Due to the strategical importance of this agricultural commodity, it is necessary to improve models that assist the crops monitoring process. Recently, remote sensing images have also been used to crops monitoring. Vegetation index images obtained by operations between satellite channels, for instance, can be taken over a season, showing the development of crops. Specialists in agrometeorology need methods which aim at understanding and mining these datasets to discover interesting patterns and knowledge. Accordingly, this paper presents a methodology to analyze NDVI time series using a distance function based on dynamic time warping distance (DTW) to perform similarity search. The experiments were done for NDVI multi-temporal images from seven harvests regarding the period from April/2001 to March/2008. NDVI time series was generated from NOAA-AVHRR images of a relevant sugar cane producer region in Brazil. Two different distance functions were compared and DTW reached better results than Euclidean distance. The proposed method allowed comparing harvests in different regions and in the same time series. Results of similarity search on NDVI time series demonstrate the efficacy of the use of distance function to similarity search in remote sensing data. This approach is appropriate to assess patterns in a long time series of multi-temporal images and can assist in the process of decision making by agricultural entrepreneurs. MenosBrazil is an important sugar cane producer, which is the main resource for ethanol production, a renewable source of energy. Due to the strategical importance of this agricultural commodity, it is necessary to improve models that assist the crops monitoring process. Recently, remote sensing images have also been used to crops monitoring. Vegetation index images obtained by operations between satellite channels, for instance, can be taken over a season, showing the development of crops. Specialists in agrometeorology need methods which aim at understanding and mining these datasets to discover interesting patterns and knowledge. Accordingly, this paper presents a methodology to analyze NDVI time series using a distance function based on dynamic time warping distance (DTW) to perform similarity search. The experiments were done for NDVI multi-temporal images from seven harvests regarding the period from April/2001 to March/2008. NDVI time series was generated from NOAA-AVHRR images of a relevant sugar cane producer region in Brazil. Two different distance functions were compared and DTW reached better results than Euclidean distance. The proposed method allowed comparing harvests in different regions and in the same time series. Results of similarity search on NDVI time series demonstrate the efficacy of the use of distance function to similarity search in remote sensing data. This approach is appropriate to assess patterns in a long time series of multi-temporal images and ca... Mostrar Tudo |
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Palavras-Chave: |
Agrometeorologia; Imagens multitemporais de NDVI; Imagens NOAA-AVHRR. |
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Thesagro: |
Agricultura; Cana de açúcar; Sensoriamento remoto. |
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Thesaurus Nal: |
Agrometeorology; Remote sensing; Sugarcane. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02571nam a2200301 a 4500
001 1256605
005 2020-01-15
008 2009 bl uuuu u00u1 u #d
100 1 $aROMANI, L. A. S.
245 $aMonitoring sugar cane crops through DTW-based method for similarity search in NDVI time series.$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. 171-178.
500 $aMultiTemp 2009.
520 $aBrazil is an important sugar cane producer, which is the main resource for ethanol production, a renewable source of energy. Due to the strategical importance of this agricultural commodity, it is necessary to improve models that assist the crops monitoring process. Recently, remote sensing images have also been used to crops monitoring. Vegetation index images obtained by operations between satellite channels, for instance, can be taken over a season, showing the development of crops. Specialists in agrometeorology need methods which aim at understanding and mining these datasets to discover interesting patterns and knowledge. Accordingly, this paper presents a methodology to analyze NDVI time series using a distance function based on dynamic time warping distance (DTW) to perform similarity search. The experiments were done for NDVI multi-temporal images from seven harvests regarding the period from April/2001 to March/2008. NDVI time series was generated from NOAA-AVHRR images of a relevant sugar cane producer region in Brazil. Two different distance functions were compared and DTW reached better results than Euclidean distance. The proposed method allowed comparing harvests in different regions and in the same time series. Results of similarity search on NDVI time series demonstrate the efficacy of the use of distance function to similarity search in remote sensing data. This approach is appropriate to assess patterns in a long time series of multi-temporal images and can assist in the process of decision making by agricultural entrepreneurs.
650 $aAgrometeorology
650 $aRemote sensing
650 $aSugarcane
650 $aAgricultura
650 $aCana de açúcar
650 $aSensoriamento remoto
653 $aAgrometeorologia
653 $aImagens multitemporais de NDVI
653 $aImagens NOAA-AVHRR
700 1 $aZULLO JÚNIOR, J.
700 1 $aNASCIMENTO, C. R.
700 1 $aGONÇALVES, R. R. V.
700 1 $aTRAINA, C
700 1 $aTRAINA, A. J. M.
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Embrapa Agricultura Digital (CNPTIA) |
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| 11. |  | LIMA, C. P. de; CUADRA, S. V.; ALMEIDA, I. R. de; STEINMETZ, S.; REISSER JUNIOR, C. Base de dados meteorológicos do laboratório de agrometeorologia da Embrapa Clima Temperado. In: ENCONTRO DE INICIAÇÃO CIENTÍFICA E PÓS-GRADUAÇÃO DA EMBRAPA CLIMA TEMPERADO, 6., 2016, Pelotas. Ciência: Empreendedorismo e inovação: anais. Brasília, DF: Embrapa, 2016. p. 180-182| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Clima Temperado. |
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| 18. | | CONCEIÇÃO, L. F. C. da; PINTO, L.; CUADRA, S. V.; ALMEIDA, I. R. de; STEINMETZ, S. Análise de variáveis meteorológicas e a relação com componentes de crescimento do arroz irrigado. In: CONGRESSO BRASILEIRO DE AGROMETEOROLOGIA, 20.; SIMPÓSIO DE MUDANÇAS CLIMÁTICAS E DESERTIFICAÇÃO DO SEMIÁRIDO BRASILEIRO, 5., 2017, Juazeiro. A agrometeorologia na solução de problemas multiescala: anais. Petrolina: Embrapa Semiárido: Univasf, 2017.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Clima Temperado. |
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| 19. | | ASSAD, E. D.; VICTORIA, D. de C.; CUADRA, S. V.; PUGLIERO, V. S.; ZANETTI, M. R. Efeito das mudanças climáticas na agricultura do Cerrado. In: BOLFE, E. L.; SANO, E. E.; CAMPOS, S. K. (Ed.). Dinâmica agrícola no cerrado: análises e projeções. Brasília, DF: Embrapa, 2020. v. 1, cap. 7, p. 213-228.| Tipo: Capítulo em Livro Técnico-Científico |
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