RELATIONSHIP BETWEEN SAMPLE DESIGN AND GEOMETRIC ANISOTROPY IN THE PREPARATION OF THEMATIC MAPS OF CHEMICAL SOIL ATTRIBUTES

ABSTRACT Spatial variability depends on the sampling configuration and characteristics associated with the georeferenced phenomenon, such as geometric anisotropy. This study aimed to determine the influence of the sampling design on parameter estimation in an anisotropic geostatistical model and the spatial estimation of a georeferenced variable at unsampled locations. Datasets were simulated with geometric anisotropy, considering five values for the anisotropic ratio (1, 2, 3, 4, 5), and three sampling designs: lattice, random and lattice plus close pairs. The simulation results were used as a reference to select anisotropic models to describe the spatial dependence structure in chemical soil properties. For each dataset (with either simulated or chemical soil properties), the values of the georeferenced variables at unsampled locations were estimated by kriging, considering estimated isotropic and anisotropic geostatistical models. The choice of the sampling design influenced the spatial estimation of the georeferenced variable and the quality of the estimation of the geostatistical anisotropic model. The incorporation of geometric anisotropy in the spatial estimation of simulated data sets and soil chemical properties produced differences in the spatial estimation and improved the level of detail of subregions in thematic maps.

Saved in:
Bibliographic Details
Main Authors: Guedes,Luciana P. C., Uribe-Opazo,Miguel A., Ribeiro Junior,Paulo J., Dalposso,Gustavo H.
Format: Digital revista
Language:English
Published: Associação Brasileira de Engenharia Agrícola 2018
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000200260
Tags: Add Tag
No Tags, Be the first to tag this record!
id oai:scielo:S0100-69162018000200260
record_format ojs
spelling oai:scielo:S0100-691620180002002602018-05-29RELATIONSHIP BETWEEN SAMPLE DESIGN AND GEOMETRIC ANISOTROPY IN THE PREPARATION OF THEMATIC MAPS OF CHEMICAL SOIL ATTRIBUTESGuedes,Luciana P. C.Uribe-Opazo,Miguel A.Ribeiro Junior,Paulo J.Dalposso,Gustavo H. bootstrap directional trend geostatistics spatial variability tests of isotropy ABSTRACT Spatial variability depends on the sampling configuration and characteristics associated with the georeferenced phenomenon, such as geometric anisotropy. This study aimed to determine the influence of the sampling design on parameter estimation in an anisotropic geostatistical model and the spatial estimation of a georeferenced variable at unsampled locations. Datasets were simulated with geometric anisotropy, considering five values for the anisotropic ratio (1, 2, 3, 4, 5), and three sampling designs: lattice, random and lattice plus close pairs. The simulation results were used as a reference to select anisotropic models to describe the spatial dependence structure in chemical soil properties. For each dataset (with either simulated or chemical soil properties), the values of the georeferenced variables at unsampled locations were estimated by kriging, considering estimated isotropic and anisotropic geostatistical models. The choice of the sampling design influenced the spatial estimation of the georeferenced variable and the quality of the estimation of the geostatistical anisotropic model. The incorporation of geometric anisotropy in the spatial estimation of simulated data sets and soil chemical properties produced differences in the spatial estimation and improved the level of detail of subregions in thematic maps.info:eu-repo/semantics/openAccessAssociação Brasileira de Engenharia AgrícolaEngenharia Agrícola v.38 n.2 20182018-04-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000200260en10.1590/1809-4430-eng.agric.v38n2p260-269/2018
institution SCIELO
collection OJS
country Brasil
countrycode BR
component Revista
access En linea
databasecode rev-scielo-br
tag revista
region America del Sur
libraryname SciELO
language English
format Digital
author Guedes,Luciana P. C.
Uribe-Opazo,Miguel A.
Ribeiro Junior,Paulo J.
Dalposso,Gustavo H.
spellingShingle Guedes,Luciana P. C.
Uribe-Opazo,Miguel A.
Ribeiro Junior,Paulo J.
Dalposso,Gustavo H.
RELATIONSHIP BETWEEN SAMPLE DESIGN AND GEOMETRIC ANISOTROPY IN THE PREPARATION OF THEMATIC MAPS OF CHEMICAL SOIL ATTRIBUTES
author_facet Guedes,Luciana P. C.
Uribe-Opazo,Miguel A.
Ribeiro Junior,Paulo J.
Dalposso,Gustavo H.
author_sort Guedes,Luciana P. C.
title RELATIONSHIP BETWEEN SAMPLE DESIGN AND GEOMETRIC ANISOTROPY IN THE PREPARATION OF THEMATIC MAPS OF CHEMICAL SOIL ATTRIBUTES
title_short RELATIONSHIP BETWEEN SAMPLE DESIGN AND GEOMETRIC ANISOTROPY IN THE PREPARATION OF THEMATIC MAPS OF CHEMICAL SOIL ATTRIBUTES
title_full RELATIONSHIP BETWEEN SAMPLE DESIGN AND GEOMETRIC ANISOTROPY IN THE PREPARATION OF THEMATIC MAPS OF CHEMICAL SOIL ATTRIBUTES
title_fullStr RELATIONSHIP BETWEEN SAMPLE DESIGN AND GEOMETRIC ANISOTROPY IN THE PREPARATION OF THEMATIC MAPS OF CHEMICAL SOIL ATTRIBUTES
title_full_unstemmed RELATIONSHIP BETWEEN SAMPLE DESIGN AND GEOMETRIC ANISOTROPY IN THE PREPARATION OF THEMATIC MAPS OF CHEMICAL SOIL ATTRIBUTES
title_sort relationship between sample design and geometric anisotropy in the preparation of thematic maps of chemical soil attributes
description ABSTRACT Spatial variability depends on the sampling configuration and characteristics associated with the georeferenced phenomenon, such as geometric anisotropy. This study aimed to determine the influence of the sampling design on parameter estimation in an anisotropic geostatistical model and the spatial estimation of a georeferenced variable at unsampled locations. Datasets were simulated with geometric anisotropy, considering five values for the anisotropic ratio (1, 2, 3, 4, 5), and three sampling designs: lattice, random and lattice plus close pairs. The simulation results were used as a reference to select anisotropic models to describe the spatial dependence structure in chemical soil properties. For each dataset (with either simulated or chemical soil properties), the values of the georeferenced variables at unsampled locations were estimated by kriging, considering estimated isotropic and anisotropic geostatistical models. The choice of the sampling design influenced the spatial estimation of the georeferenced variable and the quality of the estimation of the geostatistical anisotropic model. The incorporation of geometric anisotropy in the spatial estimation of simulated data sets and soil chemical properties produced differences in the spatial estimation and improved the level of detail of subregions in thematic maps.
publisher Associação Brasileira de Engenharia Agrícola
publishDate 2018
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000200260
work_keys_str_mv AT guedeslucianapc relationshipbetweensampledesignandgeometricanisotropyinthepreparationofthematicmapsofchemicalsoilattributes
AT uribeopazomiguela relationshipbetweensampledesignandgeometricanisotropyinthepreparationofthematicmapsofchemicalsoilattributes
AT ribeirojuniorpauloj relationshipbetweensampledesignandgeometricanisotropyinthepreparationofthematicmapsofchemicalsoilattributes
AT dalpossogustavoh relationshipbetweensampledesignandgeometricanisotropyinthepreparationofthematicmapsofchemicalsoilattributes
_version_ 1756389052855091200