Kriging: a method of interpolation for geographical information systems.
ABSTRACT Geographical information systems could be improved by adding procedures for geostatistical spatial analysis to existing facilities. Most traditional methods of interpolation are based on mathematical as distinct from stochastic models of spatial variation. Spatially distributed data behave more like random variables, however, and regionalized variable theory provides a set of stochastic methods for analysing them. Kriging is the method of interpolation deriving from regionalized variable theory. It depends on expressing spatial variation of the property in terms of the variogram, and it minimizes the prediction errors which are themselves estimated. We describe the procedures and the way we link them using standard operating systems. We illustrate them using examples from case studies, one involving the mapping and control of soil salinity in the Jordan Valley of Israel, the other in semi-arid Botswana where the herbaceous cover was estimated and mapped from aerial photographic survey.
- Journal of Soil Science. 01/1984; 35:127-140.
- 01/1992; Oxford University Press.
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ABSTRACT: Disjunctive kriging provides minimum variance estimates of properties from non-linear combinations of spatially correlated sample data. In addition it can be used to estimate the conditional probability that some critical threshold is exceeded or that there is a deficit at unsampled points. The technique has been applied to estimate and map the salinity of the soil in the Bet Shean Valley of Israel from measurements of electrical conductivity. In November 1985 the estimated electrical conductivity of the soil exceeded 4 mS per centimetre throughout most of the region, and in only a small area was the probability of salinity less than 0.2. By March 1986 the electrical conductivity had declined everywhere to less than 4 mS per centimetre, and the conditional probability of exceeding this value nowhere exceeded 0.25. Despite the fluctuation in salinity farmers seem to have it under control. The results suggest that winter wheat is likely to germinate poorly in the saltier parts of the region and that lucerne (alfalfa, Medicago sativa) is unlikely to yield its maximum over most of it. Cotton, a summer crop sown in spring, should not suffer.Soil Use and Management 01/2007; 6(3):97 - 104. · 1.83 Impact Factor