sampling, data screening, spatial covariances, the variogram and its modelling; * includes a new chapter on stochastic simulation, and covers the latest methods, such as residual maximum likelihood and factorial kriging analysis; * adopts a practical approach throughout, illustrating the applications with worked examples and case studies; * provides step-by-step guidance for analysing environmental survey data; * explains the underlying theory and rationale behind the choices faced by the researchers at each stage, allowing the reader to appreciate the assumptions and constraints involved. The accessible style of Geostatistics for Environmental Scientists, Second Edition makes this text invaluable to advanced undergraduate and graduate students of spatial variation and environmental research.