DUBLIN, Ireland–Research and Markets has announced the addition of Geostatistics for Environmental Scientists, 2nd Edition to their offering.
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.
About the Authors
Richard Webster, Rothamsted Research, Harpenden
Dr Webster is the Senior Research Fellow at Rothamsted Research.
Margaret A. Oliver, Visiting Professor, Department of Soil Science, University of Reading
Professor Oliver has taught geostatistics, applied statistics, multivariate analysis and pedology to undergraduates and postgraduates. She also established a short geostatistics course while at the University of Birmingham, which has now been taught in several countries (e.g. Sweden, USA and Mexico). She is the author of over 70 papers and two co-authored books.
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
Appendix A Aide-me´moire for Spatial Analysis
A.4 Histogram and summary
A.5 Normality and transformation
A.6 Spatial distribution
A.7 Spatial analysis: the variogram
A.8 Modelling the variogram
A.9 Spatial estimation or prediction: kriging
Appendix B GenStat Instructions for Analysis
B.1 Summary statistics
B.3 Cumulative distribution
B.5 The variogram
B.5.1 Experimental variogram
B.5.2 Fitting a model
B.7.1 Auto- and cross-variograms
B.7.2 Fitting a model of coregionalization
For more information visit http://www.researchandmarkets.com/reports/c70213