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Registro Completo |
Biblioteca(s): |
Embrapa Unidades Centrais. |
Data corrente: |
17/06/2010 |
Data da última atualização: |
17/06/2010 |
Autoria: |
COHEN, K. de O.; JACKIX, M. de N. H. |
Título: |
Efeito do processo de conchagem nas características físicas e químicas do chocolate ao letie e de produtos análogos. |
Ano de publicação: |
2009 |
Fonte/Imprenta: |
Planaltina, DF: Embrapa Cerrados, 2009. |
Páginas: |
22 p. |
Série: |
(Embrapa Cerrados. Documentos, 268). |
Idioma: |
Português |
Palavras-Chave: |
Chcolate. |
Thesagro: |
Cupuaçu; Processamento; Tecnologia de alimento. |
Categoria do assunto: |
-- |
Marc: |
LEADER 00576nam a2200181 a 4500 001 1855498 005 2010-06-17 008 2009 bl uuuu u0uu1 u #d 100 1 $aCOHEN, K. de O. 245 $aEfeito do processo de conchagem nas características físicas e químicas do chocolate ao letie e de produtos análogos. 260 $aPlanaltina, DF: Embrapa Cerrados$c2009 300 $a22 p. 490 $a(Embrapa Cerrados. Documentos, 268). 650 $aCupuaçu 650 $aProcessamento 650 $aTecnologia de alimento 653 $aChcolate 700 1 $aJACKIX, M. de N. H.
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Biblioteca(s): |
Embrapa Territorial. |
Data corrente: |
11/04/2012 |
Data da última atualização: |
18/01/2013 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 2 |
Autoria: |
LU, D.; CHEN, Q.; WANG, G.; MORAN, E.; BATISTELLA, M.; ZHANG, M.; LAURIN, G. V.; SAAH, D. |
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. |
Título: |
Aboveground forest biomass estimation with Landsat and LiDAR data and uncertainty analysis of the estimates. |
Ano de publicação: |
2012 |
Fonte/Imprenta: |
International Journal of Forestry Research, v. 2012. p. 16, 2012 |
Páginas: |
16 p. |
Idioma: |
Inglês |
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. |
Thesagro: |
Biomassa. |
Categoria do assunto: |
-- |
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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