Description

Book Synopsis
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.

Trade Review
"This is certainly an invaluable text for advanced undergraduate and graduate students of spatial variation and environmental research." (International Journal of Environmental and Analytical Chemistry, August 2008)

Table of Contents
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 for Environmental 2e Statistics in

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    A Hardback by Richard Webster, Margaret A. Oliver

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      Book details

      Publisher John Wiley & Sons Inc
      Published 5 October 2007
      ISBN-13 9780470028582
      978-0470028582
      ISBN-10 0470028580
      Also in:
      The environment Mathematics

      Description

      Book Synopsis
      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.

      Trade Review
      "This is certainly an invaluable text for advanced undergraduate and graduate students of spatial variation and environmental research." (International Journal of Environmental and Analytical Chemistry, August 2008)

      Table of Contents
      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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