University of Amsterdam, 2009. — 271 p. — ISBN 9090249818 9789090249810.Geostatistical mapping can be defined as analytical production of maps by using field observations, auxiliary information and a computer 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 soil organic carbon, species density distribution, distribution of landforms, density of DEM-derived streams, and spatiotemporal 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 geographical computing.The purpose of this guide is to assist you in producing quality maps by using fully-operational open source software packages: R+gstat/geoR and SAGA GIS.Materials presented in this book have been used for the five-day advanced training course "GEOSTAT: spatio-temporal data analysis"ContentsForeword Disclaimer Frequently Asked Questions Geostatistical mapping Regression-kriging Software (R+GIS+GE) Auxiliary data sources First steps (meuse) Heavy metal concentrations (NGS) Soil Organic Carbon (WISE_SOC) Species' occurrence records (bei) Geomorphological units (fishcamp) Stream networks (baranjahill) Land surface temperature (HRtemp)
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