Abstract:A simulação sequencial gera um conjunto de imagens equiprováveis com a mesma variabilidade espacial dos valores experimentais. O objetivo deste estudo foi analisar a dependência espacial dos atributos diagnósticos do solo e aplicar a simulação sequencial para caracterizar a distribuição de probabilidade local dos atributos e verificar as zonas de incerteza. A área de estudo, com 1.200,32 ha, compreende a fazenda experimental Edgardia da Faculdade de Ciências Agronômicas da Universidade Estadual Paulista, Botuc… Show more
“…In this sense, techniques that assess and incorporate the uncertainties associated with information from soil maps promote an advance in knowledge of mapping errors (Castrignanò et al, 2008;Brevik et al, 2016). The identification and determination of uncertainties can be performed directly on the mapping units using fuzzy logic (Zhu, 1997) and indicative simulation techniques (Silva et al, 2015), or on soil attributes, especially by means of geostatistical simulations (Grunwald et al, 2007;Castrignanò et al, 2008;Teixeira et al, 2012;Viscarra-Rossel et al, 2014) and error propagation techniques (Hengl et al, 2014).…”
Section: Introductionmentioning
confidence: 99%
“…The uncertainties determined in soil units are used to identify the probability of certain class be correctly defined (Phillips, 2013). Its use is difficult since it is necessary the knowledge of a great number of modal pedons for its determination (Silva et al, 2015). In its turn, the uncertainty in spatial assessment of soil attributes is used for identifying sites that require increased number of samples (Teixeira et al, 2012), constructing estimating scenarios (Grunwald et al, 2007), and providing an indirect measure of the estimate quality generated at each site (Viscarra-Rossel et al, 2014).…”
Section: Introductionmentioning
confidence: 99%
“…The definition of the attributes to be used in the identification of uncertainties is of great importance. Silva et al (2015) proposes the uncertainty assessment for soil diagnostic attributes (color, texture gradient, base saturation, clay and sand content and soil organic carbon). For tropical soils, soil mineralogy and clay content have great relationship with the taxonomic classes of soil (Costa et al, 1999) and directly influence the definition of mapping units (Marques Jr. et al, 2014;Siqueira et al, 2015).…”
This study aimed to use spatial uncertainty of magnetic susceptibility (MS) and clay content to improve soilmapping units. In an experimental area of 870 ha, a regular sampling grid containing 371 points was set, in which MS and clay content were assessed at a depth range of 0-0.25 m. Using a digital elevation model and field observations, a 4440-m transect was established on the study area from hilltop to the foothill, toward the gentlest slope. Standard deviation maps based on 200 realizations of the sequential gaussian simulation measured spatial estimate uncertainties. To limit transition zones along the transect, uncertainty isolines representative of the transition between soil-mapping units were selected. Both attributes presented peaks of uncertainties near the change of mapping units, previously known. Uncertainty zones, previously delineated, ranged from 45 to 210 m and from 60 to 170 m, for MS and clay content, respectively. However, after extrapolating the uncertainties to the side of the transect, amplitude changes of the uncertainty zones were observed, especially in the transition regions between landscape shape and geology. Delineation of mapping units, which incorporated the uncertainties of MS and clay content, was similar. However, due to lower cost and promptness, MS becomes the most feasible alternative. Knowing spatial uncertainties enables readjusting limits in maps of soil-mapping units and may support identification of most favorable regions for determining modal pedon representative of each unit.
“…In this sense, techniques that assess and incorporate the uncertainties associated with information from soil maps promote an advance in knowledge of mapping errors (Castrignanò et al, 2008;Brevik et al, 2016). The identification and determination of uncertainties can be performed directly on the mapping units using fuzzy logic (Zhu, 1997) and indicative simulation techniques (Silva et al, 2015), or on soil attributes, especially by means of geostatistical simulations (Grunwald et al, 2007;Castrignanò et al, 2008;Teixeira et al, 2012;Viscarra-Rossel et al, 2014) and error propagation techniques (Hengl et al, 2014).…”
Section: Introductionmentioning
confidence: 99%
“…The uncertainties determined in soil units are used to identify the probability of certain class be correctly defined (Phillips, 2013). Its use is difficult since it is necessary the knowledge of a great number of modal pedons for its determination (Silva et al, 2015). In its turn, the uncertainty in spatial assessment of soil attributes is used for identifying sites that require increased number of samples (Teixeira et al, 2012), constructing estimating scenarios (Grunwald et al, 2007), and providing an indirect measure of the estimate quality generated at each site (Viscarra-Rossel et al, 2014).…”
Section: Introductionmentioning
confidence: 99%
“…The definition of the attributes to be used in the identification of uncertainties is of great importance. Silva et al (2015) proposes the uncertainty assessment for soil diagnostic attributes (color, texture gradient, base saturation, clay and sand content and soil organic carbon). For tropical soils, soil mineralogy and clay content have great relationship with the taxonomic classes of soil (Costa et al, 1999) and directly influence the definition of mapping units (Marques Jr. et al, 2014;Siqueira et al, 2015).…”
This study aimed to use spatial uncertainty of magnetic susceptibility (MS) and clay content to improve soilmapping units. In an experimental area of 870 ha, a regular sampling grid containing 371 points was set, in which MS and clay content were assessed at a depth range of 0-0.25 m. Using a digital elevation model and field observations, a 4440-m transect was established on the study area from hilltop to the foothill, toward the gentlest slope. Standard deviation maps based on 200 realizations of the sequential gaussian simulation measured spatial estimate uncertainties. To limit transition zones along the transect, uncertainty isolines representative of the transition between soil-mapping units were selected. Both attributes presented peaks of uncertainties near the change of mapping units, previously known. Uncertainty zones, previously delineated, ranged from 45 to 210 m and from 60 to 170 m, for MS and clay content, respectively. However, after extrapolating the uncertainties to the side of the transect, amplitude changes of the uncertainty zones were observed, especially in the transition regions between landscape shape and geology. Delineation of mapping units, which incorporated the uncertainties of MS and clay content, was similar. However, due to lower cost and promptness, MS becomes the most feasible alternative. Knowing spatial uncertainties enables readjusting limits in maps of soil-mapping units and may support identification of most favorable regions for determining modal pedon representative of each unit.
“…A grande popularidade da krigagem vem do fato de que suas estimativas nos pontos não amostrados são confiáveis, ou seja, sem parcialidade e com variância mínima, bem como sem erros de excessos (Oliver & Webster, 2014). Segundo Silva et al (2015), no que se refere à interpolação de atributos do solo, a K.O. é o método mais utilizado.…”
A espacialização dos atributos do solo é de grande importância na interpretação geográfica da paisagem especialmente quando o foco desejado são as questões hidrogeológicas acerca da capacidade de infiltração da água no solo, sendo a condutividade hidráulica seu indicador direto. Assim, este trabalho buscou verificar a existência de dependência espacial para as variáveis areia, argila, silte, densidade, micro e macro porosidade, volume total de poros e condutividade hidráulica, bem como analisar sua variabilidade e sua espacialização através da Krigagem Ordinária. O estudo foi conduzido em área de planície aluvial, adjacente ao Rio Mogi Guaçu. Os resultados encontrados confirmaram a relação de dependência espacial de todos os atributos analisados na escala pesquisada e revelaram a anisotropia dos atributos condutividade hidráulica, macroporosidade e volume total de poros. Todos os atributos obtiveram seus melhores ajustes no modelo esférico. A relação direta entre macroprorosidade e condutividade hidráulica também foi verificada nas amostras coletadas, colocando a macroporosidade como um bom indicador da capacidade de infiltração em campo.
“…As alternatives for the smoothness promoted by OK and the incapacity to reproduce the uncertainties through its variance, stochastic simulations have been widely applied for the most diverse purposes in the last years, among which some stand out: simulation of distribution and spatial variability of heavy metals in the soil, for the identification of polluted areas (Lin, 2008); evaluation of uncertainties of soil chemical (Oliveira et al, 2013) and mineralogical attributes (Silva Júnior et al, 2013), and soil classes (Silva et al, 2015); construction of different scenarios of estimates for soil CO 2 (Teixeira et al, 2012) and demarcation of erosion-prone areas (Delbari et al, 2009).…”
A B S T R A C TThe aim of this study was to quantify and to map the spatial distribution and uncertainty of soil calcium (Ca) content in a sugarcane area by sequential Gaussian and simulatedannealing simulation methods. The study was conducted in the municipality of Guariba, Simulações estocásticas dos teores de cálcio em área de cana-de-açúcar R E S U M O Objetivou-se, neste trabalho, quantificar e mapear a distribuição espacial e a incerteza do teor de cálcio (Ca) do solo, em área sob o cultivo de cana-de-açúcar por meio da simulação sequencial gaussiana e simulação do arrefecimento simulado. O estudo foi conduzido no município de Guariba, nordeste do estado de São Paulo. Foi estabelecida uma malha amostral contendo 206 pontos separados por uma distância de 50 m totalizando aproximadamente 42 ha. Os teores de cálcio foram avaliados na profundidade de 0-0,20 m. Foram utilizadas técnicas geoestatísticas de estimação, krigagem ordinária e de simulações estocásticas: simulação sequencial gaussiana e a simulação de arrefecimento simulado. A técnica da krigagem ordinária não reproduz satisfatoriamente as estatísticas globais do teor de Ca. A utilização das técnicas da simulação permite a reprodução do padrão da variabilidade espacial do teor de Ca e as técnicas de simulação da sequencial gaussiana e a simulação do arrefecimento simulado mostraram variações significativas dos teores de Ca na pequena escala.
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