Takes readers through the essential steps in computing and modelling the variogram, which is often done in a black-box environment that does not lead to an understanding of the spatial variation
Short computer code to guide users in GenStat as a learning medium
Unique and succinct information
This brief will provide a bridge in succinct form between the geostatistics textbooks and the computer manuals for `push-button' practice. It is becoming increasingly important for practitioners, especially neophytes, to understand what underlies modern geostatistics and the currently available software so that they can choose sensibly and draw correct conclusions from their analysis and mapping. The brief will contain some theory, but only that needed for practitioners to understand the essential steps in analyses. It will guide readers sequentially through the stages of properly designed sampling, exploratory data analysis, variography (computing the variogram and modelling it), followed by ordinary kriging and finally mapping kriged estimates and their errors. There will be short section on trend and universal kriging. Other types of kriging will be mentioned so that readers can delve further in the substantive literature to tackle more complex tasks.
Content Level » Professional/practitioner
Keywords » Field sampling - Kriging - Spatial analysis - Spatial variation - Variogram
Related subjects » Agriculture - Ecology - Environmental Science & Engineering - Geophysics & Geodesy - Physical & Information Science
Author(s): Margaret A. Oliver, Richard Webster
Series: SpringerBriefs in Agriculture
Publisher: Springer
Year: 2015
Language: English
Pages: C, X, 100
Cover
S Title
Basic Steps in Geostatistics: The Variogram and Kriging
Copyright
© The Author(s) 2015
ISSN 2211-808X
ISSN 2211-8098 (electronic)
ISBN 978-3-319-15864-8
ISBN 978-3-319-15865-5 (eBook)
DOI 10.1007/978-3-319-15865-5
Library of Congress Control Number: 2015932443
Preface
Acknowledgments
Contents
1 Introduction
Abstract
1.1 Background to Geostatistics
1.2 Applications of Geostatistics
1.2.1 Mining and Engineering
1.2.2 Environmental Pollution
1.2.3 Precision Agriculture (PA)
1.2.4 Fisheries
1.3 Sampling
1.3.1 The Domain
1.3.2 The Variables
1.3.3 Units and Support
1.3.4 Practical Matters
1.4 The Essence of Geostatistics
2 Regionalized Variable Theory
Abstract
2.1 Random Variables and Regionalized Variable Theory
2.1.1 Stationarity
3 The Variogram and Modelling
Abstract
3.1 The Experimental Variogram
3.1.1 Computing the Variogram from Regular Sampling in One Dimension
3.1.2 Computing the Variogram from Regular and Irregular Sampling in Two Dimensions
3.2 Factors Affecting the Reliability of Experimental Variograms
3.2.1 Sample Size
3.2.2 Sampling Interval and Spatial Scale
3.2.3 Lag Interval and Bin Width
3.2.4 Statistical Distribution
3.2.5 Anisotropy
3.2.6 Trend
3.3 Modelling the Variogram
3.3.1 Principal Features of the Variogram
3.3.2 Variogram Model Functions
3.4 Factors Affecting the Reliability of Variogram Models
3.4.1 Fitting Models
4 Geostatistical Prediction: Kriging
Abstract
4.1 Introduction
4.2 Theory
4.2.1 Kriging Weights
4.2.1.1 Effect of the Ratio of the Nugget:Sill Variances
4.2.1.2 Changing the Range
4.2.1.3 Block Kriging
4.2.1.4 Kriging with Irregularly Scattered Data
4.2.2 Kriging Neighbourhood
4.2.2.1 Effect of the Kriging Neighbourhood
4.2.3 Punctual and Block Kriging for Mapping
4.2.4 Anisotropy
4.2.5 Simple Kriging
4.2.6 Lognormal Kriging
4.3 Cross-Validation
4.4 Summary
5 Sampling
Abstract
5.1 Sampling for the Variogram
5.1.1 Nested Sampling
5.1.1.1 Illustrative Example: Nested Sampling in the Wyre Forest
5.2 Sampling Plans for Mapping
5.2.1 Illustrative Example: Sampling to Map Chromium in the Swiss Jura
5.3 Summary
6 Dealing with Trend
Abstract
6.1 Trend
6.1.1 Variogram and Model
6.2 Example
6.3 Illustration from a Case Study
6.4 Summary
References
Index
