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Registro Completo |
Biblioteca(s): |
Embrapa Solos. |
Data corrente: |
01/03/2007 |
Data da última atualização: |
04/03/2020 |
Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
Autoria: |
MENDONÇA-SANTOS, M. de L.; MCBRATNEY, A. B.; MINASNY, B. |
Afiliação: |
MARIA DE LOURDES M SANTOS BREFIN, CNPS. |
Título: |
Soil prediction with spatially decomposed environmental factors. |
Ano de publicação: |
2007 |
Fonte/Imprenta: |
In: LAGACHERIE, P.; MCBRATNEY, A. B.; VOLTZ, M. (Ed.). Digital soil mapping: an introductory perspective. Amsterdam: Elsevier, 2007. cap. 21, 269-278. |
Idioma: |
Inglês |
Conteúdo: |
Prediction of soil attributes and soil classes in digital soil mapping relies on finding relationships between soil and the predictor variables of soil-forming factors and processes. The predictor variables can be remotely or proximally sensed images of soil, landscape, parent material or climatic factors. Till date, most prediction methods are based on performing regression on the predictor variables directly to predict soil attributes or classes. There are problems using data layers from different sources, particularly, multicollinearity, and the fact that the relationships between soil and environmental variables can change with spatial scale. To overcome the problem of correlation between variables, principal component analysis can be performed on the predictor variables. With respect to the spatial dependency, each of these variables can be decomposed into separate spatial components and mapped separately. One of the methods of achieving this is wavelet analysis, which decomposes the variables into separate hierarchical spatial components of decreasing spatial resolution. These components could all be derived and subsequently used as separate layers in predicting soil classes or soil attributes. In this chapter, data are decomposed using the wavelet method and examples of predictions of soil classes and surface-clay content are shown, in order to evaluate the effect of using the decomposed layers in comparison with the original data. |
Palavras-Chave: |
Atributos do solo. |
Thesagro: |
Sensoriamento Remoto. |
Thesaurus Nal: |
Remote sensing. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
Marc: |
LEADER 02099naa a2200181 a 4500 001 1338904 005 2020-03-04 008 2007 bl uuuu u00u1 u #d 100 1 $aMENDONÇA-SANTOS, M. de L. 245 $aSoil prediction with spatially decomposed environmental factors.$h[electronic resource] 260 $c2007 520 $aPrediction of soil attributes and soil classes in digital soil mapping relies on finding relationships between soil and the predictor variables of soil-forming factors and processes. The predictor variables can be remotely or proximally sensed images of soil, landscape, parent material or climatic factors. Till date, most prediction methods are based on performing regression on the predictor variables directly to predict soil attributes or classes. There are problems using data layers from different sources, particularly, multicollinearity, and the fact that the relationships between soil and environmental variables can change with spatial scale. To overcome the problem of correlation between variables, principal component analysis can be performed on the predictor variables. With respect to the spatial dependency, each of these variables can be decomposed into separate spatial components and mapped separately. One of the methods of achieving this is wavelet analysis, which decomposes the variables into separate hierarchical spatial components of decreasing spatial resolution. These components could all be derived and subsequently used as separate layers in predicting soil classes or soil attributes. In this chapter, data are decomposed using the wavelet method and examples of predictions of soil classes and surface-clay content are shown, in order to evaluate the effect of using the decomposed layers in comparison with the original data. 650 $aRemote sensing 650 $aSensoriamento Remoto 653 $aAtributos do solo 700 1 $aMCBRATNEY, A. B. 700 1 $aMINASNY, B. 773 $tIn: LAGACHERIE, P.; MCBRATNEY, A. B.; VOLTZ, M. (Ed.). Digital soil mapping: an introductory perspective. Amsterdam: Elsevier, 2007. cap. 21, 269-278.
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Embrapa Solos (CNPS) |
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Biblioteca(s): |
Embrapa Pecuária Sul. |
Data corrente: |
11/11/2014 |
Data da última atualização: |
11/11/2014 |
Tipo da produção científica: |
Resumo em Anais de Congresso |
Autoria: |
SANTOS, P. A. dos; DOMINGUES, R.; FONTES, M. R. V.; YOKOO, M. J. I.; GASPAR, E. B. |
Afiliação: |
Patrício Azevedo dos Santos, ACADÊMICO URCAMP; ROBERT DOMINGUES, CPPSUL; Milena Ramos Vaz Fontes, ACADÊMICA FURG; MARCOS JUN ITI YOKOO, CPPSUL; EMANUELLE BALDO GASPAR, CPPSUL. |
Título: |
Extração de DNA de sangue total e de leucócitos de bovinos. |
Ano de publicação: |
2014 |
Fonte/Imprenta: |
In: SIMPÓSIO DE INICIAÇÃO CIENTÍFICA DA EMBRAPA PECUÁRIA SUL, 4., 2014, Bagé. Resumos... Bagé: Embrapa Pecuária Sul, 2014. |
Páginas: |
p. 29. |
Idioma: |
Português |
Thesagro: |
Parasito. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/111380/1/Santos-et-al.pdf
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Marc: |
LEADER 00577nam a2200169 a 4500 001 1999717 005 2014-11-11 008 2014 bl uuuu u00u1 u #d 100 1 $aSANTOS, P. A. dos 245 $aExtração de DNA de sangue total e de leucócitos de bovinos.$h[electronic resource] 260 $aIn: SIMPÓSIO DE INICIAÇÃO CIENTÍFICA DA EMBRAPA PECUÁRIA SUL, 4., 2014, Bagé. Resumos... Bagé: Embrapa Pecuária Sul$c2014 300 $ap. 29. 650 $aParasito 700 1 $aDOMINGUES, R. 700 1 $aFONTES, M. R. V. 700 1 $aYOKOO, M. J. I. 700 1 $aGASPAR, E. B.
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