This material can be used for distance education or selfstudy. I've built them up over the years, and when I get a fresh idea or want to work something out for myself, I improve them or write a new tutorials.
Topics include introduction to R, working with spatial data in R, visualization of spatial data, exploring spatial structure (trend surfaces, variograms, variogram maps), interpolation, optimal interpolation (kriging), block kriging, universal kriging, kriging with external drift, indicator kriging, sequential simulation of spatial fields, sampling optimization including simulated annealing, introduction to pointpatterns, introduction to areal data, exchanging spatial data with other tools. The main computing tool was the gstat
package of the R environment; however many other packages are used (MASS, spdep, spatstat, ...
).
Course materials
These materials are offered asis, with no support. I hope you find them interesting and useful. Comments and corrections are always welcome. Materials last updated 06June2017
 Exercises using R
(Zip file of 25 PDF, 38.2 Mb)
 ex0 Preparing the computing environment
 ex1 Using the R Environment for Statistical Computing
 ex1a Supplement to ex1: ggplot2 graphics
 ex2 Visualizing spatial structure
 ex3 Modelling spatial structure from point samples
 ex4 Predicting from point samples (Part 1): Ordinary Kriging
 ex4a Normalscore transformation
 ex5 Predicting from point samples (Part 2): Kriging weights, Block kriging, Universal Kriging
 ex5a Predicting from point samples (Part 3): Using secondary information
 ex6 Assessing the quality of spatial predictions; Geostatistical simulation
 ex7 Geostatistical risk mapping
 ex8 Spatial sampling
 ex8a Spatial sampling: simulated spatial annealing
 ex9 R and GIS
 exA Change of support
 exB Compositional variables
 exC Spatiotemporal geostatistics
 exADSA Areal Data and Spatial Autocorrelation
 exPPA Pointpattern analysis
 exRKGLS Regional mapping of climate variable from point samples:
 Ordinary Least Squares trend
 Generalized Least Squares trend
 Regression Kriging with GLS trend
 Kriging with External Drift
 Random Forests
 Thinplate splines
 Thiessen polygons
 exQGIS Introduction to QGIS
 exTPS Thin plate spline interpolation
 ex_TrendSurface Trend surfaces in R by Ordinary and Generalized Least Squares
 R code for exercises
(Zip file of 40 R scripts, 92.3 Kb)
 Overheads
(Zip file of 13 PDF, 15.6 Mb)
 Datasets for exercises: Jura heavy metals, Cameroon soil properties, Sandford transect,Kansas aquifer, Northeast US climate, E. Ithaca 10 m DEM; USA 4km resolution DEM; large!! 27.2 Mb
Supplementary material
Author:
D G Rossiter

URL:
http://www.css.cornell.edu/faculty/dgr2/teach/degeostats.html

EMail:
dgr2@cornell.edu

Last modified: Wed Dec 27 11:55:17 EST 2017
