Detrending non stationary data for geostatistical applications.
Autor(a) principal: | |
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Data de Publicação: | 2010 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
Texto Completo: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/886765 |
Resumo: | The use of geostatistics requires at least that the intrinsic hypothesis be satisfied. The presence of a trend in the data invalidates this hypothesis. One of the ways of solving this problem is by subtracting a function fitted to the original data and working with the residuals. This technique also represents a change to a smaller scale of the variability and surface roughness. This paper describes the detrending technique of subtracting a trend surface fitted by the least squares method and discusses the results using topographical data as examples. The objective is to show how the detrending technique works for different scales and degrees of trend and how to interpret the results. It is shown that the simplest the surfaces fitted that does the work of removing the trend the best are the results obtained. The use of jack knifing is proved useful to validate the resulting semivariograms. For most of the applications and depending upon the scale, a linear or a parabolic surface works reasonably well. The back transformation of the data afterwards is very easily done by adding back the subtracted trend surface. |
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Detrending non stationary data for geostatistical applications.Erro reduzidoEstacionaridadeVariação de escalaScale of variationStationaritySemivariogramsTopografiaThe use of geostatistics requires at least that the intrinsic hypothesis be satisfied. The presence of a trend in the data invalidates this hypothesis. One of the ways of solving this problem is by subtracting a function fitted to the original data and working with the residuals. This technique also represents a change to a smaller scale of the variability and surface roughness. This paper describes the detrending technique of subtracting a trend surface fitted by the least squares method and discusses the results using topographical data as examples. The objective is to show how the detrending technique works for different scales and degrees of trend and how to interpret the results. It is shown that the simplest the surfaces fitted that does the work of removing the trend the best are the results obtained. The use of jack knifing is proved useful to validate the resulting semivariograms. For most of the applications and depending upon the scale, a linear or a parabolic surface works reasonably well. The back transformation of the data afterwards is very easily done by adding back the subtracted trend surface.SIDNEY ROSA VIEIRA, IAC; JOSE RUY PORTO DE CARVALHO, CNPTIA; MARCOS BACIS CEDDIA, UFRRJ; ANTONIO PAZ GONZÁLEZ, Universidade da Coruña, Espanha.VIEIRA, S. R.CARVALHO, J. R. P. deCEDDIA, M. C.PAZ GONZÁLEZ2011-04-25T11:11:11Z2011-04-25T11:11:11Z2011-04-2520102011-07-08T11:11:11Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleBragantia, Campinas, v. 69, p.1-8, 2010.http://www.alice.cnptia.embrapa.br/alice/handle/doc/886765enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2017-08-15T22:54:17Zoai:www.alice.cnptia.embrapa.br:doc/886765Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542017-08-15T22:54:17falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-08-15T22:54:17Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Detrending non stationary data for geostatistical applications. |
title |
Detrending non stationary data for geostatistical applications. |
spellingShingle |
Detrending non stationary data for geostatistical applications. VIEIRA, S. R. Erro reduzido Estacionaridade Variação de escala Scale of variation Stationarity Semivariograms Topografia |
title_short |
Detrending non stationary data for geostatistical applications. |
title_full |
Detrending non stationary data for geostatistical applications. |
title_fullStr |
Detrending non stationary data for geostatistical applications. |
title_full_unstemmed |
Detrending non stationary data for geostatistical applications. |
title_sort |
Detrending non stationary data for geostatistical applications. |
author |
VIEIRA, S. R. |
author_facet |
VIEIRA, S. R. CARVALHO, J. R. P. de CEDDIA, M. C. PAZ GONZÁLEZ |
author_role |
author |
author2 |
CARVALHO, J. R. P. de CEDDIA, M. C. PAZ GONZÁLEZ |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
SIDNEY ROSA VIEIRA, IAC; JOSE RUY PORTO DE CARVALHO, CNPTIA; MARCOS BACIS CEDDIA, UFRRJ; ANTONIO PAZ GONZÁLEZ, Universidade da Coruña, Espanha. |
dc.contributor.author.fl_str_mv |
VIEIRA, S. R. CARVALHO, J. R. P. de CEDDIA, M. C. PAZ GONZÁLEZ |
dc.subject.por.fl_str_mv |
Erro reduzido Estacionaridade Variação de escala Scale of variation Stationarity Semivariograms Topografia |
topic |
Erro reduzido Estacionaridade Variação de escala Scale of variation Stationarity Semivariograms Topografia |
description |
The use of geostatistics requires at least that the intrinsic hypothesis be satisfied. The presence of a trend in the data invalidates this hypothesis. One of the ways of solving this problem is by subtracting a function fitted to the original data and working with the residuals. This technique also represents a change to a smaller scale of the variability and surface roughness. This paper describes the detrending technique of subtracting a trend surface fitted by the least squares method and discusses the results using topographical data as examples. The objective is to show how the detrending technique works for different scales and degrees of trend and how to interpret the results. It is shown that the simplest the surfaces fitted that does the work of removing the trend the best are the results obtained. The use of jack knifing is proved useful to validate the resulting semivariograms. For most of the applications and depending upon the scale, a linear or a parabolic surface works reasonably well. The back transformation of the data afterwards is very easily done by adding back the subtracted trend surface. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010 2011-04-25T11:11:11Z 2011-04-25T11:11:11Z 2011-04-25 2011-07-08T11:11:11Z |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Bragantia, Campinas, v. 69, p.1-8, 2010. http://www.alice.cnptia.embrapa.br/alice/handle/doc/886765 |
identifier_str_mv |
Bragantia, Campinas, v. 69, p.1-8, 2010. |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/886765 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
collection |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
repository.name.fl_str_mv |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
cg-riaa@embrapa.br |
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1794503343733735424 |