Geostatistics for environmental scientists.

--Preface
1.- Introduction
2.- Basic Statistics
3.- Prediction and Interpolation
4.- Characterizing Spatial Processes: The Covariance and Variogram
5.- Modelling the Variogram
6.- Reliability of the Experimental Variogram and Nested Sampling
7.- Spectral Analysis
8.- Local Estimation or Prediction: Kriging
9.- Kriging in the Presence of Trend and Factorial Kriging
10.- Cross-Correlation, Coregionalization and Cokriging
11.- Disjunctive Kriging
12.- Stochastic Simulation (new file)
--Appendix A
--Appendix B
--References
--Index

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.