There are many factors that environmental scientists should consider in their research. Weather and climate vary widely between locations, soil varies at every spatial scale at which it is examined, and even man-made attributes, such as the distribution of pollution, fluctuate significantly.

Geostatistics is essential for environmental scientists. Weather and climate vary from place to place, soil varies at every scale at which it is examined, and even man-made attributes - such as the distribution of pollution - vary. The techniques used in geostatistics are ideally suited to the needs of environmental scientists, who use them to make the best of sparse data for prediction, and top plan future surveys when resources are limited. Geostatistical technology has advanced much in the last few years and many of these developments are being incorporated into the practitioner's repertoire. This second edition describes these techniques for environmental scientists. Topics such as stochastic simulation, sampling, data screening, spatial covariances, the variogram and its modeling, and spatial prediction by kriging are described in rich detail. At each stage the underlying theory is fully explained, and the rationale behind the choices given, allowing the reader to appreciate the assumptions and constraints involved.

Preface1 Introduction2 Basic Statistics3 Prediction and Interpolation4 Characterizing Spatial Processes: The Covariance and Variogram5 Modelling the Variogram6 Reliability of the Experimental Variogram and Nested Sampling7 Spectral Analysis8 Local Estimation or Prediction: Kriging9 Kriging in the Presence of Trend and Factorial Kriging10 Cross-Correlation, Coregionalization and Cokriging11 Disjunctive Kriging12 Stochastic Simulation (new file)Appendix AAppendix BReferencesIndex