A Practical Guide To Geostatistical Mapping Of Environmental Variables

A Practical Guide to Geostatistical Mapping of Environmental Variables Tomislav Hengl EUR 22904 EN - 2007 The mission of the Institute for Environment and Sustainability is to provide scientific-technical support to the European Union’s Policies for the protection and sustainable development of the European and global environment. European Commission Joint Research Centre Institute for Environment and Sustainability Contact information: Address: JRC Ispra, Via E. Fermi 1, I-21020 Ispra (VA), Italy Tel.: +39- 0332-785349 Fax: +39- 0332-786394 http://ies.jrc.ec.europa.eu http://www.jrc.ec.europa.eu Legal Notice Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use which might be made of this publication. A great deal of additional information on the European Union is available on the Internet. It can be accessed through the Europa server http://europa.eu JRC 38153 EUR 22904 EN ISBN 978-92-79-06904-8 ISSN 1018-5593 Luxembourg: Office for Official Publications of the European Communities © European Communities, 2007 Non-commercial reproduction and dissemination of the work as a whole freely permitted if this original copyright notice is included. To adapt or translate please contact the author. Printed in Italy A Practical Guide to Geostatistical Mapping of Environmental Variables by T. Hengl September 2007 Contents 1 Theoretical backgrounds 1.1 Basic concepts . . . . . . . . . . . . . 1.1.1 Environmental variables . . . . 1.1.2 Aspects of spatial variability . 1.1.3 Spatial prediction models . . . 1.2 Mechanical spatial prediction models . 1.2.1 Inverse distance interpolation . 1.2.2 Regression on coordinates . . . 1.2.3 Splines . . . . . . . . . . . . . . 1.3 Statistical spatial prediction models . 1.3.1 Kriging . . . . . . . . . . . . . 1.3.2 Environmental correlation . . . 1.3.3 Predicting from polygon maps 1.3.4 Mixed or hybrid models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1 2 3 8 11 11 12 13 13 14 20 23 24 2 Regression-kriging 2.1 The Best Linear Unbiased Predictor of spatial data . . . 2.1.1 Selecting the right spatial prediction technique . 2.1.2 Universal kriging, kriging with external drift . . 2.1.3 A simple example of regression-kriging . . . . . . 2.2 Local versus localized models . . . . . . . . . . . . . . . 2.3 Spatial prediction of categorical variables . . . . . . . . 2.4 Geostatistical simulations . . . . . . . . . . . . . . . . . 2.5 Spatio-temporal regression-kriging . . . . . . . . . . . . 2.6 Sampling strategies and optimisation algorithms . . . . 2.7 Fields of application . . . . . . . . . . . . . . . . . . . . 2.7.1 Soil mapping applications . . . . . . . . . . . . . 2.7.2 Interpolation of climatic and meteorological data 2.7.3 Mapping plant and animal species . . . . . . . . 2.8 Final notes about regression-kriging . . . . . . . . . . . 2.8.1 Alternatives to RK . . . . . . . . . . . . . . . . . 2.8.2 Limitations of RK . . . . . . . . . . . . . . . . . 2.8.3 Beyond RK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 27 30