Detrending non stationary data for geostatistical applications.

Detalhes bibliográficos
Autor(a) principal: VIEIRA, S. R.
Data de Publicação: 2010
Outros Autores: CARVALHO, J. R. P. de, CEDDIA, M. C., PAZ GONZÁLEZ
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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spelling 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
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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)
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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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