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ordinary kriging 40% 70%
universal kriging
A Practical Guide to
Geostatistical Mapping
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178440 181560 178440 181560
Tomislav Hengl
Fig. . Mapping uncertainty for zinc visualized using whitening: ordinary kriging (left) and universal kriging
(right). Predicted values in log-scale.
A Practical Guide to Geostatistical Mapping Guide to A Practical
Geostatistical mapping can be defined as analytical production of maps by using field
observations, auxiliary information and puter program that calculates values at
locations of interest. The purpose of this guide is to assist you in producing quality maps by
using fully-operational open source software packages. It will first introduce you to the
basic principles of geostatistical mapping and regression-kriging, as the key prediction
technique, then it will guide you through software tools – R+gstat/geoR, SAGA GIS and
Google Earth – which will be used to prepare the data, run analysis and make final layouts.
Geostatistical mapping is further illustrated using seven diverse case studies: interpolation
of soil parameters, heavy metal concentrations, global anic carbon, species density
distribution, distribution of landforms, density of DEM-derived streams, and spatio-
temporal interpolation of land surface temperatures. Unlike other books from the “use R”
series, or purely GIS user manuals, this book specifically aims at bridging the gaps between
statistical and puting.
Materials presented in this book have been used for the five-day advanced training course
“GEOSTAT: spatio-temporal data analysis with R+SAGA+Google Earth”, that is periodically
organized by the author and collaborators.
Visit the book's homepage to obtain a copy of the data sets and scripts used in the exercises:
http://spatial-/book/
Get involved: join the R-sig-geo mailing list!
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