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Sample adequately to estimate variograms of soil properties
Author(s) -
WEBSTER R.,
OLIVER M. A.
Publication year - 1992
Publication title -
journal of soil science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.244
H-Index - 111
eISSN - 1365-2389
pISSN - 0022-4588
DOI - 10.1111/j.1365-2389.1992.tb00128.x
Subject(s) - variogram , statistics , confidence interval , sample (material) , sampling (signal processing) , geostatistics , data set , percentile , mathematics , soil science , spatial variability , environmental science , kriging , computer science , chemistry , filter (signal processing) , chromatography , computer vision
SUMMARY The variogram is central in the spatial analysis of soil, yet it is often estimated from few data, and its precision is unknown because confidence limits cannot be determined analytically from a single set of data. Approximate confidence intervals for the variogram of a soil property can be found numerically by simulating a large field of values using a plausible model and then taking many samples from it and computing the observed variogram of each sample. A sampling distribution of the variogram and its percentiles can then be obtained. When this is done for situations typical in soil and environmental surveys it seems that variograms computed on fewer than 50 data are of little value and that at least 100 data are needed. Our experiments suggest that for a normally distributed isotropic variable a variogram computed from a sample of 150 data might often be satisfactory, while one derived from 225 data will usually be reliable.