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Journal ArticleDOI

How geostatistics can help you

Margaret A. Oliver, +1 more
- 01 Dec 1991 - 
- Vol. 7, Iss: 4, pp 206-217
TLDR
The variogram is crucial in all geostatistics; it can be used not only in the estimation itself but also to choose additional sampling sites, improve a monitoring network or design an optimal sampling scheme for a survey as discussed by the authors.
Abstract
. Geostatistics is basically a technology for estimating the local values of properties that vary in space from sample data. Research and development in the last 15 years has shown it to be eminently suited for soil and ripe for application in soil survey and land management. The basic technique, ordinary kriging, provides unbiased estimates with minimum and known variance. Data for related variables can be incorporated to improve estimates using cokriging. By more elaborate analysis using disjunctive kriging the probabilities of deficiency and excess can be estimated to aid decision. The variogram is crucial in all geostatistics; it must be estimated reliably from sufficient data at a sensible scale and modelled properly. Once obtained it can be used not only in the estimation itself but also to choose additional sampling sites, improve a monitoring network or design an optimal sampling scheme for a survey. It may also be used to control a multivariate classification so that the resulting classes are not too fragmented spatially to manage.

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Citations
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Journal ArticleDOI

The study of metal contamination in urban soils of Hong Kong using a GIS-based approach.

TL;DR: Several hot-spot areas of metal contamination were identified from the composite metal geochemical map, mainly in the old industrial and residential areas, and the Pb isotope composition of the contaminated soils showed clear anthropogenic origins.
Journal ArticleDOI

Scaling-up crop models for climate variability applications.

TL;DR: In this paper, a case study of soybean in the state of Georgia in the USA illustrates several crop model scaling approaches, including sampling input variability in geographic or probability space, and calibration of model inputs or outputs.
Journal ArticleDOI

Geostatistics and remote sensing

TL;DR: This article introduces these applications of geostatistics and uses two examples to highlight characteristics that are common to them all and concludes with a discussion of conditional simulation as a novelGeostatistical technique for use in remote sensing.
Journal ArticleDOI

Mapping Soil Test Phosphorus and Potassium for Variable-Rate Fertilizer Application

TL;DR: The objectives of the study were to evaluate cell (area) vs. point soil rumpling, both on a grid basis, and compare methods for mapping location specific soil test data.
References
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Journal ArticleDOI

A General Coefficient of Similarity and Some of Its Properties

John C. Gower
- 01 Dec 1971 - 
TL;DR: A general coefficient measuring the similarity between two sampling units is defined and the matrix of similarities between all pairs of sample units is shown to be positive semidefinite.
Journal ArticleDOI

Optimal interpolation and isarithmic mapping of soil properties. II. Block kriging.

TL;DR: In this paper, the average values of soil properties over areas rather than point values can be obtained by block kriging, and the maps of sodium and stone content at Plas Gogerddan, Central Wales, kriged over blocks 920m2, and thickness of cover loam at Hole Farm, Norfolk, krng over blocks of 400m2.
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Optimal interpolation and isarithmic mapping of soil properties. I. The semi-variogram and punctual kriging

TL;DR: Kriging as mentioned in this paper is a form of weighted local averaging, which is optimal in the sense that it provides estimates of values at unrecorded places without bias and with minimum and known variance.
Journal ArticleDOI

Choosing functions for semi‐variograms of soil properties and fitting them to sampling estimates

TL;DR: In this article, the Akaike information criterion is recommended for selecting the best model from several plausible ones to describe the observed variation in soil, though for kriging it may be desirable to validate the chosen model.
Journal ArticleDOI

An empirical law describing heterogeneity in the yields of agricultural crops

TL;DR: In this article, it was shown that the above law can be generalized to any size of field by applying a certain adjustment to the regression coefficient b', so as to give a modified coefficient b applicable to an infinite field.
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