Scaling of semivariograms and the kriging estimation of field-measured properties

Detalhes bibliográficos
Autor(a) principal: Vieira,S. R.
Data de Publicação: 1997
Outros Autores: Tillotson,P. M., Biggar,J. W., Nielsen,D. R.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Brasileira de Ciência do Solo (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06831997000400001
Resumo: Two methods were evaluated for scaling a set of semivariograms into a unified function for kriging estimation of field-measured properties. Scaling is performed using sample variances and sills of individual semivariograms as scale factors. Theoretical developments show that kriging weights are independent of the scaling factor which appears simply as a constant multiplying both sides of the kriging equations. The scaling techniques were applied to four sets of semivariograms representing spatial scales of 30 x 30 m to 600 x 900 km. Experimental semivariograms in each set successfully coalesced into a single curve by variances and sills of individual semivariograms. To evaluate the scaling techniques, kriged estimates derived from scaled semivariogram models were compared with those derived from unscaled models. Differences in kriged estimates of the order of 5% were found for the cases in which the scaling technique was not successful in coalescing the individual semivariograms, which also means that the spatial variability of these properties is different. The proposed scaling techniques enhance interpretation of semivariograms when a variety of measurements are made at the same location. They also reduce computational times for kriging estimations because kriging weights only need to be calculated for one variable. Weights remain unchanged for all other variables in the data set whose semivariograms are scaled.
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spelling Scaling of semivariograms and the kriging estimation of field-measured propertiessemivariogramscalingkrigingspatial variabilityTwo methods were evaluated for scaling a set of semivariograms into a unified function for kriging estimation of field-measured properties. Scaling is performed using sample variances and sills of individual semivariograms as scale factors. Theoretical developments show that kriging weights are independent of the scaling factor which appears simply as a constant multiplying both sides of the kriging equations. The scaling techniques were applied to four sets of semivariograms representing spatial scales of 30 x 30 m to 600 x 900 km. Experimental semivariograms in each set successfully coalesced into a single curve by variances and sills of individual semivariograms. To evaluate the scaling techniques, kriged estimates derived from scaled semivariogram models were compared with those derived from unscaled models. Differences in kriged estimates of the order of 5% were found for the cases in which the scaling technique was not successful in coalescing the individual semivariograms, which also means that the spatial variability of these properties is different. The proposed scaling techniques enhance interpretation of semivariograms when a variety of measurements are made at the same location. They also reduce computational times for kriging estimations because kriging weights only need to be calculated for one variable. Weights remain unchanged for all other variables in the data set whose semivariograms are scaled.Sociedade Brasileira de Ciência do Solo1997-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06831997000400001Revista Brasileira de Ciência do Solo v.21 n.4 1997reponame:Revista Brasileira de Ciência do Solo (Online)instname:Sociedade Brasileira de Ciência do Solo (SBCS)instacron:SBCS10.1590/S0100-06831997000400001info:eu-repo/semantics/openAccessVieira,S. R.Tillotson,P. M.Biggar,J. W.Nielsen,D. R.eng2014-10-08T00:00:00Zoai:scielo:S0100-06831997000400001Revistahttp://www.scielo.br/scielo.php?script=sci_serial&pid=0100-0683&lng=es&nrm=isohttps://old.scielo.br/oai/scielo-oai.php||sbcs@ufv.br1806-96570100-0683opendoar:2014-10-08T00:00Revista Brasileira de Ciência do Solo (Online) - Sociedade Brasileira de Ciência do Solo (SBCS)false
dc.title.none.fl_str_mv Scaling of semivariograms and the kriging estimation of field-measured properties
title Scaling of semivariograms and the kriging estimation of field-measured properties
spellingShingle Scaling of semivariograms and the kriging estimation of field-measured properties
Vieira,S. R.
semivariogram
scaling
kriging
spatial variability
title_short Scaling of semivariograms and the kriging estimation of field-measured properties
title_full Scaling of semivariograms and the kriging estimation of field-measured properties
title_fullStr Scaling of semivariograms and the kriging estimation of field-measured properties
title_full_unstemmed Scaling of semivariograms and the kriging estimation of field-measured properties
title_sort Scaling of semivariograms and the kriging estimation of field-measured properties
author Vieira,S. R.
author_facet Vieira,S. R.
Tillotson,P. M.
Biggar,J. W.
Nielsen,D. R.
author_role author
author2 Tillotson,P. M.
Biggar,J. W.
Nielsen,D. R.
author2_role author
author
author
dc.contributor.author.fl_str_mv Vieira,S. R.
Tillotson,P. M.
Biggar,J. W.
Nielsen,D. R.
dc.subject.por.fl_str_mv semivariogram
scaling
kriging
spatial variability
topic semivariogram
scaling
kriging
spatial variability
description Two methods were evaluated for scaling a set of semivariograms into a unified function for kriging estimation of field-measured properties. Scaling is performed using sample variances and sills of individual semivariograms as scale factors. Theoretical developments show that kriging weights are independent of the scaling factor which appears simply as a constant multiplying both sides of the kriging equations. The scaling techniques were applied to four sets of semivariograms representing spatial scales of 30 x 30 m to 600 x 900 km. Experimental semivariograms in each set successfully coalesced into a single curve by variances and sills of individual semivariograms. To evaluate the scaling techniques, kriged estimates derived from scaled semivariogram models were compared with those derived from unscaled models. Differences in kriged estimates of the order of 5% were found for the cases in which the scaling technique was not successful in coalescing the individual semivariograms, which also means that the spatial variability of these properties is different. The proposed scaling techniques enhance interpretation of semivariograms when a variety of measurements are made at the same location. They also reduce computational times for kriging estimations because kriging weights only need to be calculated for one variable. Weights remain unchanged for all other variables in the data set whose semivariograms are scaled.
publishDate 1997
dc.date.none.fl_str_mv 1997-12-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06831997000400001
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06831997000400001
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0100-06831997000400001
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Ciência do Solo
publisher.none.fl_str_mv Sociedade Brasileira de Ciência do Solo
dc.source.none.fl_str_mv Revista Brasileira de Ciência do Solo v.21 n.4 1997
reponame:Revista Brasileira de Ciência do Solo (Online)
instname:Sociedade Brasileira de Ciência do Solo (SBCS)
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instname_str Sociedade Brasileira de Ciência do Solo (SBCS)
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institution SBCS
reponame_str Revista Brasileira de Ciência do Solo (Online)
collection Revista Brasileira de Ciência do Solo (Online)
repository.name.fl_str_mv Revista Brasileira de Ciência do Solo (Online) - Sociedade Brasileira de Ciência do Solo (SBCS)
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