Geostatistical-based index for spatial variability in soil properties

Detalhes bibliográficos
Autor(a) principal: Appel Neto,Edemar
Data de Publicação: 2020
Outros Autores: Seidel Junior,Enio, Oliveira,Marcelo Silva de
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=S0100-06832020000100305
Resumo: ABSTRACT The assessment of spatial variability of environmental variables such as soil properties is important for site-specific management. A geostatistical index that allows quantifying and characterizing the structure of spatial variability is fundamental in this context. Thus, this study aimed to develop a new spatial dependency index, called the Spatial Dependence Measure (SDM) for the spherical, exponential, Gaussian, cubic, pentaspherical, and wave semivariogram models; and comparing it with some of the indexes available in the literature. The SDM is also dimensionless, in the same way as the Spatial Dependence Index (SDI), also considering more parameters of the semivariogram, when compared to the Spatial Dependence Degree (SPD) and Relative Nugget Effect (NE) indexes. In a simulation data study, it is observed that the SDI and SDM indexes showed an advantage over the SPD (or NE). To exemplify the application of the SDM in the proposal for the classification of soil properties, we used estimates of geostatistical parameters presented in the two studies. The results indicate that the SDM can be a measure that, analyzed together with the SDI, can help to improve the description of the spatial variability structure. Thus, this study expands the number of geostatisitcal-based measures and increases the power of decision on the description of the degree of spatial variability of agricultural and soil attributes.
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spelling Geostatistical-based index for spatial variability in soil propertieswithin-field variabilityspatial dependenceautocorrelationsemivariogramABSTRACT The assessment of spatial variability of environmental variables such as soil properties is important for site-specific management. A geostatistical index that allows quantifying and characterizing the structure of spatial variability is fundamental in this context. Thus, this study aimed to develop a new spatial dependency index, called the Spatial Dependence Measure (SDM) for the spherical, exponential, Gaussian, cubic, pentaspherical, and wave semivariogram models; and comparing it with some of the indexes available in the literature. The SDM is also dimensionless, in the same way as the Spatial Dependence Index (SDI), also considering more parameters of the semivariogram, when compared to the Spatial Dependence Degree (SPD) and Relative Nugget Effect (NE) indexes. In a simulation data study, it is observed that the SDI and SDM indexes showed an advantage over the SPD (or NE). To exemplify the application of the SDM in the proposal for the classification of soil properties, we used estimates of geostatistical parameters presented in the two studies. The results indicate that the SDM can be a measure that, analyzed together with the SDI, can help to improve the description of the spatial variability structure. Thus, this study expands the number of geostatisitcal-based measures and increases the power of decision on the description of the degree of spatial variability of agricultural and soil attributes.Sociedade Brasileira de Ciência do Solo2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832020000100305Revista Brasileira de Ciência do Solo v.44 2020reponame:Revista Brasileira de Ciência do Solo (Online)instname:Sociedade Brasileira de Ciência do Solo (SBCS)instacron:SBCS10.36783/18069657rbcs20200086info:eu-repo/semantics/openAccessAppel Neto,EdemarSeidel Junior,EnioOliveira,Marcelo Silva deeng2020-11-24T00:00:00Zoai:scielo:S0100-06832020000100305Revistahttp://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:2020-11-24T00:00Revista Brasileira de Ciência do Solo (Online) - Sociedade Brasileira de Ciência do Solo (SBCS)false
dc.title.none.fl_str_mv Geostatistical-based index for spatial variability in soil properties
title Geostatistical-based index for spatial variability in soil properties
spellingShingle Geostatistical-based index for spatial variability in soil properties
Appel Neto,Edemar
within-field variability
spatial dependence
autocorrelation
semivariogram
title_short Geostatistical-based index for spatial variability in soil properties
title_full Geostatistical-based index for spatial variability in soil properties
title_fullStr Geostatistical-based index for spatial variability in soil properties
title_full_unstemmed Geostatistical-based index for spatial variability in soil properties
title_sort Geostatistical-based index for spatial variability in soil properties
author Appel Neto,Edemar
author_facet Appel Neto,Edemar
Seidel Junior,Enio
Oliveira,Marcelo Silva de
author_role author
author2 Seidel Junior,Enio
Oliveira,Marcelo Silva de
author2_role author
author
dc.contributor.author.fl_str_mv Appel Neto,Edemar
Seidel Junior,Enio
Oliveira,Marcelo Silva de
dc.subject.por.fl_str_mv within-field variability
spatial dependence
autocorrelation
semivariogram
topic within-field variability
spatial dependence
autocorrelation
semivariogram
description ABSTRACT The assessment of spatial variability of environmental variables such as soil properties is important for site-specific management. A geostatistical index that allows quantifying and characterizing the structure of spatial variability is fundamental in this context. Thus, this study aimed to develop a new spatial dependency index, called the Spatial Dependence Measure (SDM) for the spherical, exponential, Gaussian, cubic, pentaspherical, and wave semivariogram models; and comparing it with some of the indexes available in the literature. The SDM is also dimensionless, in the same way as the Spatial Dependence Index (SDI), also considering more parameters of the semivariogram, when compared to the Spatial Dependence Degree (SPD) and Relative Nugget Effect (NE) indexes. In a simulation data study, it is observed that the SDI and SDM indexes showed an advantage over the SPD (or NE). To exemplify the application of the SDM in the proposal for the classification of soil properties, we used estimates of geostatistical parameters presented in the two studies. The results indicate that the SDM can be a measure that, analyzed together with the SDI, can help to improve the description of the spatial variability structure. Thus, this study expands the number of geostatisitcal-based measures and increases the power of decision on the description of the degree of spatial variability of agricultural and soil attributes.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
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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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832020000100305
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832020000100305
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.36783/18069657rbcs20200086
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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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.44 2020
reponame:Revista Brasileira de Ciência do Solo (Online)
instname:Sociedade Brasileira de Ciência do Solo (SBCS)
instacron:SBCS
instname_str Sociedade Brasileira de Ciência do Solo (SBCS)
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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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