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Registro Completo |
Biblioteca(s): |
Embrapa Agricultura Digital. |
Data corrente: |
04/10/2011 |
Data da última atualização: |
24/01/2020 |
Tipo da produção científica: |
Artigo em Anais de Congresso |
Autoria: |
AGUIAR, D. A.; ADAMI, M.; SILVA, W. F.; RUDORFF, B. F. T.; MELLO, M. P.; SILVA, J. dos S. V. da. |
Afiliação: |
DANIEL ALVES AGUIAR, INPE; MARCOS ADAMI, INPE; WAGNER FERNANDO SILVA, INPE; BERNARDO FRIEDRICH THEODOR RUDORFF, INPE; MARCIO PUPIN MELLO, INPE; JOÃO DOS SANTOS VILA DA SILVA, CNPTIA. |
Título: |
MODIS time series to assess pasture land. |
Ano de publicação: |
2010 |
Fonte/Imprenta: |
In: INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2010, Honolulu. Remote sensing: global vision for local action. [S.l.]: IEEE, 2010. |
Páginas: |
p. 2123-2126. |
Idioma: |
Inglês |
Notas: |
IGARSS 2010. |
Conteúdo: |
Land use conversion is a key factor in the mitigation of GHG emission. Maximum mitigation can be achieved when degraded pasture land is converted to biofuel crops. Remote sensing images, and in particular the MODIS time series data, have a great potential to asses degraded pasture land. This work has the objective to identify pasture land and its different levels of degradation in Mato Grosso do Sul state, Brazil. MODIS time series were used to obtain vegetation indices and fraction images. The wavelet technique was applied at various levels of decomposition to extract the input parameters in the WEKA J48 classifier. Pasture land was well distinguished from Cerrado. The distinction among different pasture land presented lower performance with best results for pasture with invasive plants followed by good pasture. Pasture land with bare soil patches and termite mounds were not distinguished from other classes of pasture. made it possible to reduce pasture land without herd reduction. Consequently more land became available for sugarcane. Considering that land use change is a key factor for the benefit of biofuel production to mitigate carbon emission, this benefit can be even higher if sugarcane expansion occurs on degraded pasture land. Remote sensing images have a great potential to evaluate degraded pasture land although is not a trivial task and requires intensive fieldwork. MODIS time series data transformed into vegetation indices or linear spectral mixing model are suitable to represent different pasture land conditions. Under these considerations this work has the objective to use MODIS time series to identify pasture land and its different levels of degradation in Mato Grosso do Sul state, Brazil. MenosLand use conversion is a key factor in the mitigation of GHG emission. Maximum mitigation can be achieved when degraded pasture land is converted to biofuel crops. Remote sensing images, and in particular the MODIS time series data, have a great potential to asses degraded pasture land. This work has the objective to identify pasture land and its different levels of degradation in Mato Grosso do Sul state, Brazil. MODIS time series were used to obtain vegetation indices and fraction images. The wavelet technique was applied at various levels of decomposition to extract the input parameters in the WEKA J48 classifier. Pasture land was well distinguished from Cerrado. The distinction among different pasture land presented lower performance with best results for pasture with invasive plants followed by good pasture. Pasture land with bare soil patches and termite mounds were not distinguished from other classes of pasture. made it possible to reduce pasture land without herd reduction. Consequently more land became available for sugarcane. Considering that land use change is a key factor for the benefit of biofuel production to mitigate carbon emission, this benefit can be even higher if sugarcane expansion occurs on degraded pasture land. Remote sensing images have a great potential to evaluate degraded pasture land although is not a trivial task and requires intensive fieldwork. MODIS time series data transformed into vegetation indices or linear spectral mixing model are sui... Mostrar Tudo |
Palavras-Chave: |
Degradação de pastagem; Séries temporais MODIS. |
Thesaurus Nal: |
Degradation; Pastures; Time series analysis. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
Marc: |
LEADER 02529nam a2200253 a 4500 001 1902230 005 2020-01-24 008 2010 bl uuuu u00u1 u #d 100 1 $aAGUIAR, D. A. 245 $aMODIS time series to assess pasture land.$h[electronic resource] 260 $aIn: INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2010, Honolulu. Remote sensing: global vision for local action. [S.l.]: IEEE$c2010 300 $ap. 2123-2126. 500 $aIGARSS 2010. 520 $aLand use conversion is a key factor in the mitigation of GHG emission. Maximum mitigation can be achieved when degraded pasture land is converted to biofuel crops. Remote sensing images, and in particular the MODIS time series data, have a great potential to asses degraded pasture land. This work has the objective to identify pasture land and its different levels of degradation in Mato Grosso do Sul state, Brazil. MODIS time series were used to obtain vegetation indices and fraction images. The wavelet technique was applied at various levels of decomposition to extract the input parameters in the WEKA J48 classifier. Pasture land was well distinguished from Cerrado. The distinction among different pasture land presented lower performance with best results for pasture with invasive plants followed by good pasture. Pasture land with bare soil patches and termite mounds were not distinguished from other classes of pasture. made it possible to reduce pasture land without herd reduction. Consequently more land became available for sugarcane. Considering that land use change is a key factor for the benefit of biofuel production to mitigate carbon emission, this benefit can be even higher if sugarcane expansion occurs on degraded pasture land. Remote sensing images have a great potential to evaluate degraded pasture land although is not a trivial task and requires intensive fieldwork. MODIS time series data transformed into vegetation indices or linear spectral mixing model are suitable to represent different pasture land conditions. Under these considerations this work has the objective to use MODIS time series to identify pasture land and its different levels of degradation in Mato Grosso do Sul state, Brazil. 650 $aDegradation 650 $aPastures 650 $aTime series analysis 653 $aDegradação de pastagem 653 $aSéries temporais MODIS 700 1 $aADAMI, M. 700 1 $aSILVA, W. F. 700 1 $aRUDORFF, B. F. T. 700 1 $aMELLO, M. P. 700 1 $aSILVA, J. dos S. V. da
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Embrapa Agricultura Digital (CNPTIA) |
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Biblioteca(s): |
Embrapa Florestas. |
Data corrente: |
17/08/2007 |
Data da última atualização: |
30/03/2015 |
Tipo da produção científica: |
Artigo em Anais de Congresso / Nota Técnica |
Autoria: |
PEDROZO, C. A.; BARBOSA, M. H. P.; SILVA, F. L. da; LEITE, M. S. de O.; RESENDE, M. D. V. de. |
Afiliação: |
Cássia Ângela Pedrozo, UFV/Doutorando; Márcio Henrique Pereira Barbosa, UFV; Felipe Lopes da Silva, UFV/Doutorando; Mauro Sérgio de Oliveira Leite, UFV/Mestrando; Marcos Deon Vilela de Resende, Embrapa Florestas. |
Título: |
Eficiência da seleção em fases iniciais do melhoramento da cana-de-açúcar. |
Ano de publicação: |
2007 |
Fonte/Imprenta: |
In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 4., 2007, São Lourenço. Melhoramento de plantas e agronegócio: anais. Lavras: UFLA: SBMP, 2007. |
Páginas: |
1-3. |
Descrição Física: |
1 CD-ROM. |
Idioma: |
Inglês |
Palavras-Chave: |
Cana-de-açúcar. |
Thesagro: |
Melhoramento; Seleção. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/106667/1/EficienciaSelecao0001.pdf
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Marc: |
LEADER 00697nam a2200193 a 4500 001 1312265 005 2015-03-30 008 2007 bl uuuu u00u1 u #d 100 1 $aPEDROZO, C. A. 245 $aEficiência da seleção em fases iniciais do melhoramento da cana-de-açúcar.$h[electronic resource] 260 $aIn: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 4., 2007, São Lourenço. Melhoramento de plantas e agronegócio: anais. Lavras: UFLA: SBMP$c2007 300 $a1-3.$c1 CD-ROM. 650 $aMelhoramento 650 $aSeleção 653 $aCana-de-açúcar 700 1 $aBARBOSA, M. H. P. 700 1 $aSILVA, F. L. da 700 1 $aLEITE, M. S. de O. 700 1 $aRESENDE, M. D. V. de
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