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This brief will provide a bridge in succinct form between the geostatistics textbooks and the computer manuals for `push-button´ practice. It is becoming increasingly important for practitioners, especially neophytes, to understand what underlies modern geostatistics and the currently available software so that they can choose sensibly and draw correct conclusions from their analysis and mapping. The brief will contain some theory, but only that needed for practitioners to understand the essential steps in analyses. It will guide readers sequentially through the stages of properly designed sampling, exploratory data analysis, variography (computing the variogram and modelling it), followed by ordinary kriging and finally mapping kriged estimates and their errors. There will be short section on trend and universal kriging. Other types of kriging will be mentioned so that readers can delve further in the substantive literature to tackle more complex tasks.

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1. Introduction
1.1. Background to Geostatistics
1.2. Applications of geostatistics
1.2.1. Mining and Engineering
1.2.2. Environmental Pollution
1.2.3. Precision Agriculture
1.2.4. Fisheries
1.3. Sampling
1.3.1. The Domain
1.3.2. The Variables
1.3.3. Units and Support
1.3.4. Practical Matters
1.4. The Essence of Geostatistics
2. Regionalized Variable Theory
2.1. Random Variables and Regionalized Variable Theory
2.1.1. Stationarity
3. The Variogram and Modelling
3.1. The Experimental Variogram
3.1.1. Computing the Variogram from Regular Sampling in One Dimension
3.1.2. Computing the Variogram from Sampling in Two Dimensions
3.2. Factors Affecting the Reliability of Experimental Variograms
3.2.1. Sample Size
3.2.2. Sampling Interval and Spatial Scale
3.2.3. Lag Interval and Bin Width
3.2.4. Statistical Distribution
3.2.5. Anisotropy
3.2.6. Trend
3.3. Modelling the Variogram
3.3.1. Principal Features of the Variogram
3.3.2. Variogram Model Functions
3.4. Factors Affecting the Reliability of Variogram Models
3.4.1. Fitting Models
4. Geostatistical Prediction: Kriging
4.1. Introduction
4.2. Theory
4.2.1. Kriging Weights
4.2.1.1. Effect of the Ratio of the Nugget:Sill Variances
4.2.1.2. Changing the Range
4.2.1.3. Block Kriging
4.2.1.4. Kriging with Irregularly Scattered Data
4.2.2. Kriging Neighbourhood
4.2.2.1. Effect of the Kriging Neighbourhood
4.2.3. Punctual and Block Kriging for Mapping
4.2.4. Anisotropy
4.2.5. Simple Kriging
4.2.6. Lognormal Kriging
4.3. Cross-validation
4.4. Summary
5. Sampling
5.1. Sampling for the Variogram
5.1.1. Nested Sampling
5.1.1.1. Illustrative Example: Nested Sampling in the Wyre Forest
5.2. Sampling Plans for Mapping
5.2.1. Illustrative Example: Sampling to Map Chromium in the Swiss Jura
5.3. Summary
6. Dealing with Trend
6.1. Trend
6.1.1. Variogram and Model
6.2. Example
6.3. Illustration from a Case Study
6.4. Summary

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"This text provides a condensed introduction to the fundamental principles, albeit better suited to reader from a mathematical background ... . its greatest value may be as a concise reference." (Markus Eichhorn, Frontiers of Biogeography, Vol. 7 (3), 2015)
"This text provides a condensed introduction to the fundamental principles, albeit better suited to reader from a mathematical background ... . its greatest value may be as a concise reference." (Markus Eichhorn, Frontiers of Biogeography, Vol. 7 (3), 2015)

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Richard Webster zählt weltweit zu den größten Experten, was das Thema Engel anbelangt.Er ist einer der erfolgreichsten amerikanischen Autoren und lebt mit seiner Familie in Neuseeland.

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