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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
05/08/2011 |
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Data da última atualização: |
02/04/2013 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
ANTUNES, J. F. G.; ESQUERDO, J. C. D. M.; LAMPARELLI, R. A. C. |
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Afiliação: |
JOÃO FRANCISCO GONÇALVES ANTUNES, CNPTIA; JÚLIO CÉSAR DALLA MORA ESQUERDO, CNPTIA; RUBENS AUGUSTO CAMARGO LAMPARELLI, Cepagri/Unicamp. |
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Título: |
Monitoring the temporal dynamics of four vegetation cover types from the Pantanal using the wavelet transform applied to a time-series of EVI/MODIS data. |
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Ano de publicação: |
2011 |
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Fonte/Imprenta: |
Geografia, Rio Claro, v. 36, p. 173-185, jun. 2011. |
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Idioma: |
Inglês |
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Notas: |
Número especial. |
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Conteúdo: |
Although one of the most preserved ecosystems in Brazil, the Pantanal suffers under problems such as fire, deforestation and changes in the flood and drought cycles. Monitoring all the extension of the Pantanal is essential to detect problems related to land use changes and to infer on the level of floods in the wetlands. The objective of this study was to monitor four areas in the Pantanal with different vegetation cover using the Wavelet Transform applied to a time-series of EVI (Enhanced Vegetation Index) acquired from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor, between 2005 and 2009, in order to analyze the vegetation phenology dynamics. The results showed that the Coiflet Wavelet Transform of 4th order with 90% power, was able to remove the high frequency noise and highlight the changes of the vegetation phenology with a higher precision, allowing a better analysis of trends in the inter-annual variability of EVI. Changes of the temporal EVI pattern may indicate changes in vegetation phenology, mainly due to rainfall seasonality. The technique is robust and can be extrapolated to other regions of the Pantanal in order to detect deforestation and fire occurrences. |
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Palavras-Chave: |
Detecção da fenologia; Image processing; Índice de vegetação; Perfil temporal; Processamento de imagens; Séries temporais de dados EVI/MODIS. |
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Thesagro: |
Sensoriamento Remoto. |
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Thesaurus Nal: |
Phenology; Remote sensing; Time series analysis. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/39254/1/artigo-13.pdf
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Marc: |
LEADER 02141naa a2200277 a 4500
001 1897363
005 2013-04-02
008 2011 bl uuuu u00u1 u #d
100 1 $aANTUNES, J. F. G.
245 $aMonitoring the temporal dynamics of four vegetation cover types from the Pantanal using the wavelet transform applied to a time-series of EVI/MODIS data.$h[electronic resource]
260 $c2011
500 $aNúmero especial.
520 $aAlthough one of the most preserved ecosystems in Brazil, the Pantanal suffers under problems such as fire, deforestation and changes in the flood and drought cycles. Monitoring all the extension of the Pantanal is essential to detect problems related to land use changes and to infer on the level of floods in the wetlands. The objective of this study was to monitor four areas in the Pantanal with different vegetation cover using the Wavelet Transform applied to a time-series of EVI (Enhanced Vegetation Index) acquired from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor, between 2005 and 2009, in order to analyze the vegetation phenology dynamics. The results showed that the Coiflet Wavelet Transform of 4th order with 90% power, was able to remove the high frequency noise and highlight the changes of the vegetation phenology with a higher precision, allowing a better analysis of trends in the inter-annual variability of EVI. Changes of the temporal EVI pattern may indicate changes in vegetation phenology, mainly due to rainfall seasonality. The technique is robust and can be extrapolated to other regions of the Pantanal in order to detect deforestation and fire occurrences.
650 $aPhenology
650 $aRemote sensing
650 $aTime series analysis
650 $aSensoriamento Remoto
653 $aDetecção da fenologia
653 $aImage processing
653 $aÍndice de vegetação
653 $aPerfil temporal
653 $aProcessamento de imagens
653 $aSéries temporais de dados EVI/MODIS
700 1 $aESQUERDO, J. C. D. M.
700 1 $aLAMPARELLI, R. A. C.
773 $tGeografia, Rio Claro$gv. 36, p. 173-185, jun. 2011.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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| Registros recuperados : 163 | |
| 96. |  | TAVARES, A. S.; FELIX, F. C.; COUTINHO, A. C.; ANTUNES, J. F. G.; ESQUERDO, J. C. D. M. Aprendizado de máquina e uso de séries temporais de imagens Sentinel-2 no monitoramento da cobertura e uso da terra. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 20., 2023, Florianópolis. Anais [...]. São José dos Campos: Instituto Nacional de Pesquisas Espaciais, 2023. p. 2029-2032. Editores: Douglas Francisco Marcolino Gherardi, Ieda Del´Arco Sanches, Luiz Eduardo Oliveira e Cruz de Aragão.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
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| 99. | | OLDONI, L. V.; CATTANI, C. E. V.; MERCANTE, E.; JOHANN, J. A.; ANTUNES, J. F. G.; ALMEIDA, L. Annual cropland mapping using data mining and OLI Landsat-8. Revista Brasileira de Engenharia Agrícola e Ambiental, Campina Grande, v. 23, n. 12, p. 952-958, 2019.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Agricultura Digital. |
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| 100. | | CALABONI, A.; BERTOLO, L. S.; ESQUERDO, J. C. D. M.; ANTUNES, J. F. G.; COUTINHO, A. C. Classificação digital para identificação e mapeamento de vegetação secundária e pastagens no Cerrado. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 20., 2023, Florianópolis. Anais [...]. São José dos Campos: Instituto Nacional de Pesquisas Espaciais, 2023. p. 936-939. Editores: Douglas Francisco Marcolino Gherardi, Ieda Del´Arco Sanches, Luiz Eduardo Oliveira e Cruz de Aragão.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
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| Registros recuperados : 163 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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