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| Registros recuperados : 7 | |
| 1. |  | BONELLI, E. A.; BONFIM-SILVA, E. M.; CABRAL, C. E. A.; CAMPOS, J. J.; SCARAMUZZA, W. L. M. P.; POLIZEL, A. C. Compactação do solo: Efeitos nas características produtivas e morfológicas dos capins Piatã e Mombaça. Revista Brasileira de Engenharia Agrícola e Ambiental, v. 15, n. 3, p. 264-269, mar., 2011.| Biblioteca(s): Embrapa Algodão. |
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| 2. | | AVELINO, A. C. D.; FARIA, D. A. de; CABRAL, C. E. A.; ABREU, J. G. de; CAMILI, E. C.; SALES, K. C.; BUNGENSTAB, D. J. Maximum contact Ttime of "Piatã Grass" Brachiaria brizantha (Poaceae) seeds with fertilizer for germination. Journal of Experimental Agriculture International, v. 35, n. 1, p. 1-9, 2019| Biblioteca(s): Embrapa Gado de Corte. |
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| 3. | | MOREIRA G. M.; ABREU, J. G. de; ALMEIDA, R. G. de; BARROS, L. V. de; AZEVEDO, V. H. de; SILVA NETO, I. M. da; CABRAL, C. E. A.; HERRERA, L. D. S.; PEIXOTO, W. M.; HERRERA, D. M. Sorghum intercropped with Piatã Grass in eucalyptus sub-forest. Journal of Experimental Agriculture International, v. 37, n. 1, p.1-9, 2019, article JEAI.49086.| Biblioteca(s): Embrapa Gado de Corte. |
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| 4. | | MOREIRA, G. M.; ALMEIDA, R. G. de; ABREU, J. G. de; RODRIGUES, J. A.; ALMEIDA, E. M. de; HERRERA, D. M.; CABRAL, C. E. A.; DOERZBACHER, A. L. S.; ASSIS, L. M. B.; BARBOSA JUNIOR, J. B. Características fitométricas de sorgo consorciado com capim-piatã em sub-bosque de eucalipto. In:In: CONGRESSO BRASILEIRO DE SISTEMAS INTEGRADOS DE PRODUÇÃO AGROPECUÁRIA, 2.; ENCONTRO DE INTEGRAÇÃO LAVOURA-PECUÁRIA DO SUL DE MATO GROSSO, 2., Rondonópolis, 2018. Anais eletrônicos... Mato Grosso: UFMT, 2018.| Biblioteca(s): Embrapa Gado de Corte. |
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| 5. | | REIS, R. H. P. dos; ABREU, J. G. de; ALMEIDA, R. G. de; CABRAL, L. da S.; BARROS, L. V. de; CABRAL, C. E. A.; BEHLING NETO, A.; MATTER, E.; ROYER, P. O.; HERRERA, D. M.; FARIAS, J. de M. Agronomic Characteristics, Chemical Composition and In vitro Gas Production of Sugarcane Cultivars (Saccharum spp.) for Feeding Ruminants. Journal of Experimental Agriculture International, v. 35, n. 1, p. 1-8, 2019.| Biblioteca(s): Embrapa Gado de Corte. |
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| 6. | | MONTEIRO, I. J. G.; ABREU, J. G. de; CABRAL, L. da S.; ALMEIDA, R. G. de; REIS, R. H. P. dos; BEHLING NETO, A.; CABRAL, C. E. A.; BARROS, L. V. de; AVELINO, A. C. D.; PENSO, S. Ensilagem de capim elefante acrescida de casca de soja ou farelo de arroz. Semina. ciências agrárias, Londrina, v. 37, n. 6, p. 4203-4212, nov./dez. 2016. Título em inglês: Ensiling of elephant grass with soybean hulls or rie bran.| Biblioteca(s): Embrapa Gado de Corte. |
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| 7. | | FAVARE, H. G. de; ABREU, J. G. de; BARROS, L. V. de; SILVA, F. G. da; FERREIRA, L. M. M.; BARELLI, M. A. A.; SILVA NETO, I. M. da; CABRAL, C. E. A.; PEIXOTO, W. M.; CAMPOS, F. I. da S.; LEDO, F. J. da S.; SILVA, V. Q. R. da; HERRERA, L. D. S. Effect of Elephant Grass Genotypes to Bioenergy Production. Journal of Experimental Agriculture International, v. 38, n. 1, article JEAI.49640, 2019.| Biblioteca(s): Embrapa Agrossilvipastoril; Embrapa Gado de Leite. |
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| Registros recuperados : 7 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Territorial. |
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Data corrente: |
11/04/2012 |
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Data da última atualização: |
18/01/2013 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 2 |
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Autoria: |
LU, D.; CHEN, Q.; WANG, G.; MORAN, E.; BATISTELLA, M.; ZHANG, M.; LAURIN, G. V.; SAAH, D. |
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Afiliação: |
DENGSHENG LU, INDIANA UNIVERSITY; QI CHEN, ZHEJIANG A&F UNIVERSITY; GUANGXING WANG, SOUTHERN ILLINOIS UNIVERSITY AT CARBONDALE; EMILIO MORAN, INDIANA UNIVERSITY; MATEUS BATISTELLA, CNPM; MAOZHEN ZHANG, ZHEJIANG A&F UNIVERSITY; GAIA VAGLIO LAURIN, UNIVERSITY OF TOR VERGATA; DAVID SAAH, SPATIAL INFORMATICS GROUP. |
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Título: |
Aboveground forest biomass estimation with Landsat and LiDAR data and uncertainty analysis of the estimates. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
International Journal of Forestry Research, v. 2012. p. 16, 2012 |
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Páginas: |
16 p. |
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Idioma: |
Inglês |
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Conteúdo: |
Landsat Thematic mapper (TM) image has long been the dominate data source, and recently LiDAR has offered an important new structural data stream for forest biomass estimations. On the other hand, forest biomass uncertainty analysis research has only recently obtained sufficient attention due to the difficulty in collecting reference data. This paper provides a brief overview of current forest biomass estimation methods using both TM and LiDAR data. A case study is then presented that demonstrates the forest biomass estimation methods and uncertainty analysis. Results indicate that Landsat TM data can provide adequate biomass estimates for secondary succession but are not suitable for mature forest biomass estimates due to data saturation problems. LiDAR can overcome TM?s shortcoming providing better biomass estimation performance but has not been extensively applied in practice due to data availability constraints. The uncertainty analysis indicates that various sources affect the performance of forest biomass/carbon estimation. With that said, the clear dominate sources of uncertainty are the variation of input sample plot data and data saturation problem related to optical sensors. A possible solution to increasing the confidence in forest biomass estimates is to integrate the strengths of multisensor data. |
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Thesagro: |
Biomassa. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/57333/1/MateusFR.pdf
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|
Marc: |
LEADER 01955naa a2200229 a 4500
001 1922003
005 2013-01-18
008 2012 bl uuuu u00u1 u #d
100 1 $aLU, D.
245 $aAboveground forest biomass estimation with Landsat and LiDAR data and uncertainty analysis of the estimates.
260 $c2012
300 $a16 p.
520 $aLandsat Thematic mapper (TM) image has long been the dominate data source, and recently LiDAR has offered an important new structural data stream for forest biomass estimations. On the other hand, forest biomass uncertainty analysis research has only recently obtained sufficient attention due to the difficulty in collecting reference data. This paper provides a brief overview of current forest biomass estimation methods using both TM and LiDAR data. A case study is then presented that demonstrates the forest biomass estimation methods and uncertainty analysis. Results indicate that Landsat TM data can provide adequate biomass estimates for secondary succession but are not suitable for mature forest biomass estimates due to data saturation problems. LiDAR can overcome TM?s shortcoming providing better biomass estimation performance but has not been extensively applied in practice due to data availability constraints. The uncertainty analysis indicates that various sources affect the performance of forest biomass/carbon estimation. With that said, the clear dominate sources of uncertainty are the variation of input sample plot data and data saturation problem related to optical sensors. A possible solution to increasing the confidence in forest biomass estimates is to integrate the strengths of multisensor data.
650 $aBiomassa
700 1 $aCHEN, Q.
700 1 $aWANG, G.
700 1 $aMORAN, E.
700 1 $aBATISTELLA, M.
700 1 $aZHANG, M.
700 1 $aLAURIN, G. V.
700 1 $aSAAH, D.
773 $tInternational Journal of Forestry Research$gv. 2012. p. 16, 2012
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Embrapa Territorial (CNPM) |
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