
Geostatistics for Environmental Scientists
by Webster, Richard; Oliver, Margaret A.Buy New
Rent Textbook
Rent Digital
Used Textbook
We're Sorry
Sold Out
How Marketplace Works:
- This item is offered by an independent seller and not shipped from our warehouse
- Item details like edition and cover design may differ from our description; see seller's comments before ordering.
- Sellers much confirm and ship within two business days; otherwise, the order will be cancelled and refunded.
- Marketplace purchases cannot be returned to eCampus.com. Contact the seller directly for inquiries; if no response within two days, contact customer service.
- Additional shipping costs apply to Marketplace purchases. Review shipping costs at checkout.
Summary
Author Biography
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.
Table of Contents
Preface | p. xi |
Introduction | p. 1 |
Why geostatistics? | p. 1 |
Generalizing | p. 2 |
Description | p. 5 |
Interpretation | p. 5 |
Control | p. 5 |
A little history | p. 6 |
Finding your way | p. 8 |
Basic Statistics | p. 11 |
Measurement and summary | p. 11 |
Notation | p. 12 |
Representing variation | p. 13 |
The centre | p. 15 |
Dispersion | p. 16 |
The normal distribution | p. 18 |
Covariance and correlation | p. 19 |
Transformations | p. 20 |
Logarithmic transformation | p. 21 |
Square root transformation | p. 21 |
Angular transformation | p. 22 |
Logit transformation | p. 22 |
Exploratory data analysis and display | p. 22 |
Spatial aspects | p. 25 |
Sampling and estimation | p. 26 |
Target population and units | p. 28 |
Simple random sampling | p. 28 |
Confidence limits | p. 29 |
Student's t | p. 30 |
The x[superscript 2] distribution | p. 31 |
Central limit theorem | p. 32 |
Increasing precision and efficiency | p. 32 |
Soil classification | p. 35 |
Prediction and Interpolation | p. 37 |
Spatial interpolation | p. 37 |
Thiessen polygons (Voronoi polygons, Dirichlet tessellation) | p. 38 |
Triangulation | p. 38 |
Natural neighbour interpolation | p. 39 |
Inverse functions of distance | p. 40 |
Trend surfaces | p. 40 |
Splines | p. 42 |
Spatial classification and predicting from soil maps | p. 42 |
Theory | p. 43 |
Summary | p. 45 |
Characterizing Spatial Processes: The Covariance and Variogram | p. 47 |
Introduction | p. 47 |
A stochastic approach to spatial variation: the theory of regionalized variables | p. 48 |
Random variables | p. 48 |
Random functions | p. 49 |
Spatial covariance | p. 50 |
Stationarity | p. 52 |
Ergodicity | p. 53 |
The covariance function | p. 53 |
Intrinsic variation and the variogram | p. 54 |
Equivalence with covariance | p. 54 |
Quasi-stationarity | p. 55 |
Characteristics of the spatial correlation functions | p. 55 |
Which variogram? | p. 60 |
Support and Krige's relation | p. 60 |
Regularization | p. 63 |
Estimating semivariances and covariances | p. 65 |
The variogram cloud | p. 65 |
h-Scattergrams | p. 66 |
Average semivariances | p. 67 |
The experimental covariance function | p. 73 |
Modelling the Variogram | p. 77 |
Limitations on variogram functions | p. 79 |
Mathematical constraints | p. 79 |
Behaviour near the origin | p. 80 |
Behaviour towards infinity | p. 82 |
Authorized models | p. 82 |
Unbounded random variation | p. 83 |
Bounded models | p. 84 |
Combining models | p. 95 |
Periodicity | p. 97 |
Anisotropy | p. 99 |
Fitting models | p. 101 |
What weights? | p. 104 |
How complex? | p. 105 |
Reliability of the Experimental Variogram and Nested Sampling | p. 109 |
Reliability of the experimental variogram | p. 109 |
Statistical distribution | p. 109 |
Sample size and design | p. 119 |
Sample spacing | p. 126 |
Theory of nested sampling and analysis | p. 127 |
Link with regionalized variable theory | p. 128 |
Case study: Youden and Mehlich's survey | p. 129 |
Unequal sampling | p. 131 |
Case study: Wyre Forest survey | p. 134 |
Summary | p. 138 |
Spectral Analysis | p. 139 |
Linear sequences | p. 139 |
Gilgai transect | p. 140 |
Power spectra | p. 142 |
Estimating the spectrum | p. 144 |
Smoothing characteristics of windows | p. 148 |
Confidence | p. 149 |
Spectral analysis of the Caragabal transect | p. 150 |
Bandwidths and confidence intervals for Caragabal | p. 150 |
Further reading on spectral analysis | p. 152 |
Local Estimation or Prediction: Kriging | p. 153 |
General characteristics of kriging | p. 154 |
Kinds of kriging | p. 154 |
Theory of ordinary kriging | p. 155 |
Weights | p. 159 |
Examples | p. 160 |
Kriging at the centre of the lattice | p. 161 |
Kriging off-centre in the lattice and at a sampling point | p. 169 |
Kriging from irregularly spaced data | p. 172 |
Neighbourhood | p. 172 |
Ordinary kriging for mapping | p. 174 |
Case study | p. 175 |
Kriging with known measurement error | p. 180 |
Summary | p. 180 |
Regional estimation | p. 181 |
Simple kriging | p. 183 |
Lognormal kriging | p. 185 |
Optimal sampling for mapping | p. 186 |
Isotropic variation | p. 188 |
Anisotropic variation | p. 190 |
Cross-validation | p. 191 |
Scatter and regression | p. 193 |
Kriging in the Presence of Trend and Factorial Kriging | p. 195 |
Non-stationarity in the mean | p. 195 |
Some background | p. 196 |
Application of residual maximum likelihood | p. 200 |
Estimation of the variogram by REML | p. 200 |
Practicalities | p. 203 |
Kriging with external drift | p. 203 |
Case study | p. 205 |
Factorial kriging analysis | p. 212 |
Nested variation | p. 212 |
Theory | p. 212 |
Kriging analysis | p. 213 |
Illustration | p. 218 |
Cross-Correlation, Coregionalization and Cokriging | p. 219 |
Introduction | p. 219 |
Estimating and modelling the cross-correlation | p. 222 |
Intrinsic coregionalization | p. 224 |
Example: CEDAR Farm | p. 226 |
Cokriging | p. 228 |
Is cokriging worth the trouble? | p. 231 |
Example of benefits of cokriging | p. 232 |
Principal components of coregionalization matrices | p. 235 |
Pseudo-cross-variogram | p. 241 |
Disjunctive Kriging | p. 243 |
Introduction | p. 243 |
The indicator approach | p. 246 |
Indicator coding | p. 246 |
Indicator variograms | p. 247 |
Indicator kriging | p. 249 |
Disjunctive kriging | p. 251 |
Assumptions of Gaussian disjunctive kriging | p. 251 |
Hermite polynomials | p. 252 |
Disjunctive kriging for a Hermite polynomial | p. 254 |
Estimation variance | p. 256 |
Conditional probability | p. 256 |
Change of support | p. 257 |
Case study | p. 257 |
Other case studies | p. 263 |
Summary | p. 266 |
Stochastic Simulation | p. 267 |
Introduction | p. 267 |
Simulation from a random process | p. 268 |
Unconditional simulation | p. 270 |
Conditional simulation | p. 270 |
Technicalities | p. 271 |
Lower-upper decomposition | p. 272 |
Sequential Gaussian simulation | p. 273 |
Simulated annealing | p. 274 |
Simulation by turning bands | p. 276 |
Algorithms | p. 277 |
Uses of simulated fields | p. 277 |
Illustration | p. 278 |
Aide-memoire for Spatial Analysis | p. 285 |
Introduction | p. 285 |
Notation | p. 285 |
Screening | p. 285 |
Histogram and summary | p. 286 |
Normality and transformation | p. 287 |
Spatial distribution | p. 288 |
Spatial analysis: the variogram | p. 288 |
Modelling the variogram | p. 290 |
Spatial estimation or prediction: kriging | p. 291 |
Mapping | p. 292 |
GenStat Instructions for Analysis | p. 293 |
Summary statistics | p. 293 |
Histogram | p. 294 |
Cumulative distribution | p. 294 |
Posting | p. 295 |
The variogram | p. 295 |
Experimental variogram | p. 295 |
Fitting a model | p. 296 |
Kriging | p. 297 |
Coregionalization | p. 297 |
Auto- and cross-variograms | p. 297 |
Fitting a model of coregionalization | p. 298 |
Cokriging | p. 298 |
Control | p. 298 |
References | p. 299 |
Index | p. 309 |
Table of Contents provided by Ingram. All Rights Reserved. |
An electronic version of this book is available through VitalSource.
This book is viewable on PC, Mac, iPhone, iPad, iPod Touch, and most smartphones.
By purchasing, you will be able to view this book online, as well as download it, for the chosen number of days.
Digital License
You are licensing a digital product for a set duration. Durations are set forth in the product description, with "Lifetime" typically meaning five (5) years of online access and permanent download to a supported device. All licenses are non-transferable.
More details can be found here.
A downloadable version of this book is available through the eCampus Reader or compatible Adobe readers.
Applications are available on iOS, Android, PC, Mac, and Windows Mobile platforms.
Please view the compatibility matrix prior to purchase.