Jack knifing for semivariogram validation

Abstract

The semivariogram function fitting is the most important aspect of geostatistics and because of this the model chosen must be validated. Jack knifing may be one the most efficient ways for this validation purpose. The objective of this study was to show the use of the jack knifing technique to validate geostatistical hypothesis and semivariogram models. For that purpose, topographical heights data obtained from six distinct field scales and sampling densities were analyzed. Because the topographical data showed very strong trend for all fields as it was verified by the absence of a sill in the experimental semivariograms, the trend was removed with a trend surface fitted by minimum square deviation. Semivariogram models were fitted with different techniques and the results of the jack knifing with them were compared. The jack knifing parameters analyzed were the intercept, slope and correlation coefficient between measured and estimated values, and the mean and variance of the errors calculated by the difference between measured and estimated values, divided by the square root of the estimation variances. The ideal numbers of neighbors used in each estimation was also studied using the jack knifing procedure. The jack knifing results were useful in the judgment of the adequate models fitted independent of the scale and sampling densities. It was concluded that the manual fitted semivariogram models produced better jack knifing parameters because the user has the freedom to choose a better fit in distinct regions of the semivariogram.Key words: Semivariograms, stationarity, topography, scale of variation. RESUMO JACK KNIFING PARA VALIDAÇÃO DE SEMIVARIOGRAMASA função de ajuste do semivariograma é o aspecto mais importante da geoestatística, por esse motivo, o modelo escolhido deve ser validado. Jack knifing pode ser um dos métodos mais eficientes para esta finalidade. O objetivo deste estudo foi mostrar o uso da técnica jack knifing para validar modelos de hipótese geoestatística e de semivariograma. Para essa finalidade, foram analisados dados topográficos de seis campos de escalas distintas e de diferentes densidades de amostragem. Devido aos dados topográficos selecionados terem apresentado tendência em todos os campos, fato verificado pela ausência de patamar no semivariograma, a tendência foi removida através do ajuste de uma superfície de tendência pelo método dos quadrados mínimos. Os modelos de semivariograma foram ajustados por diferentes técnicas e validados pela comparação dos resultados do jack knifing. Os parâmetros de Jack knifing analisados foram a interseção, o coeficiente angular e o coeficiente de correlação para a regressão linear entre valores estimados e medidos, e a média e a variância dos erros calculados pela diferença entre valores medidos e estimados divididos pela raiz quadrada da variância da estimativa. Os resultados do jack knifing foram úteis no julgamento adequado dos modelos ajustados aos semivariogramas, independentemente da escala e da densidade de amostragem. Conclui-se ...

Spatial variability of soil properties and cotton yield in the Brazilian Cerrado

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Analiza geostatističnega modela površja za višinsko transformacijo gps: študija primera na območju Izmirja v Turčiji

“…This is also known as the jack-knifing technique (Tomczak, 1998;Goncalves, 2006;Soycan and Soycan 2009;Vieira et al, 2010) based on removing of random data from sampling data points, and using the remaining data to perform the interpolation.…”

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