Webster / Oliver | Geostatistics for Environmental Scientists | Buch | 978-0-470-02858-2 | sack.de

Buch, Englisch, 330 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 635 g

Reihe: Statistics in Practice

Webster / Oliver

Geostatistics for Environmental Scientists

Buch, Englisch, 330 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 635 g

Reihe: Statistics in Practice

ISBN: 978-0-470-02858-2
Verlag: Wiley


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. To analyse the varied kinds of data and to predict at unvisited places from them, research scientists need to be familiar with the techniques of Geostatistics.

This revised and fully updated second edition of Geostatistics for Environmental Scientists provides comprehensive coverage of the techniques involved in this vital branch of statistics. The book

* introduces readers to the most up-to-date statistical techniques, including, 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.
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Weitere Infos & Material


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


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