1. Introduction -- 1.1. Background to Geostatistics -- 1.2. Applications of geostatistics -- 1.3. Sampling -- 1.4. The Essence of Geostatistics -- 2. Regionalized Variable Theory -- 2.1. Random Variables and Regionalized Variable Theory -- 3. The Variogram and Modelling -- 3.1. The Experimental Variogram -- 3.2. Factors Affecting the Reliability of Experimental Variograms -- 3.3. Modelling the Variogram -- 3.4. Factors Affecting the Reliability of Variogram Models -- 4. Geostatistical Prediction: Kriging -- 4.1. Introduction -- 4.2. Theory -- 4.3. Cross-validation -- 4.4. Summary -- 5. Sampling -- 5.1. Sampling for the Variogram -- 5.2. Sampling Plans for Mapping -- 5.3. Summary -- 6. Dealing with Trend -- 6.1. Trend -- 6.2. Example -- 6.3. Illustration from a Case Study -- 6.4. Summary.

This brief will provide a bridge in succinct form between the geostatistics textbooks and the computer manuals for `push-button' practice.Â{u0274} 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.Â{u2820} 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.Â{u03F4}her types of kriging will be mentioned so that readers can delve further in the substantive literature to tackle more complex tasks.