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Hengl T. A Practical Guide to Geostatistical Mapping of Environmental Variables

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Hengl T. A Practical Guide to Geostatistical Mapping of Environmental Variables
Ispra (Italy): EC JRC, 2007. — 165 p. — (Institute for Environment and Sustainability: JRC Scientific and Technical Reports) — ISBN: 9279069047.
The main purpose of this guide is to assist you in using geostatistical tools with your own data. The book assists you in obtaining the software and making the first steps, warn what might be the bottlenecks and what you should avoid doing, and provide the most crucial tricks’n’tips on how to build scripts and organize the data processing.
The guide consists of four chapters. The first chapter is an introductory chapter to the practice of geostatistical mapping and gives an overview of the spatial prediction techniques. The second chapter zooms into regression-kriging and its characteristics, advantages and limitations. The third chapter is completely dedicated to installation and doing first steps in the software, and the last, fourth, chapter gives a step-by-step guide through analysis and generation of final layouts by using a digital soil mapping case study.
After reading the first chapter, you should understand what the geostatistical mapping is; after reading the second chapter, you should know how to select the right spatial prediction technique for your application; after reading the third chapter, you should be able to install all packages used in the handbook and be aware of their capabilities; and after reading the fourth chapter, you should know how to run geostatistical mapping, prepare final layouts and interpret the results of analysis for your own case study.
Frequently Asked Questions
Theoretical backgrounds
Basic concepts
Mechanical spatial prediction models
Statistical spatial prediction models
Regress ion-kriging
The Best Linear Unbiased Predictor of spatial data
Local versus localized models
Spatial prediction of categorical variables
Geostatistical simulations
Spatio-temporal regress ion-kriging
Sampling strategies and optimisation algorithms
Fields of application
Final notes about regress ion-kriging
Hands-on software
Overview and installation of software
Geostatistics in ILWIS
Geostatistics in SAGA GIS
Geostatistics with gstat
Visualisation of maps in Google Earth
Other software options
Summary points
A geostatistical mapping exercise
Case study: Ebergotzen
Data import and preparation of maps
Regression modelling
Variogram modelling
Predictions and simulations
Assessing the quality of predictions
Comparison of predictions using various inputs
Visualization of the outputs
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