gstat (version 0.9-4)

jura: Jura data set

Description

The jura data set from Pierre Goovaerts book (see references below). It contains four data.frames: prediction.dat, validation.dat and transect.dat and juragrid.dat, and three data.frames with consistently coded land use and rock type factors. The examples below show how to transform these into spatial (sp) objects.

Usage

data(jura)

References

Goovaerts, P. 1997. Geostatistics for Natural Resources Evaluation. Oxford Univ. Press, New-York, 483 p. Appendix C describes (and gives) the Jura data set.

Atteia, O., Dubois, J.-P., Webster, R., 1994, Geostatistical analysis of soil contamination in the Swiss Jura: Environmental Pollution 86, 315-327

Webster, R., Atteia, O., Dubois, J.-P., 1994, Coregionalization of trace metals in the soil in the Swiss Jura: European Journal of Soil Science 45, 205-218

Examples

data(jura)
summary(prediction.dat)
summary(validation.dat)
summary(transect.dat)
summary(juragrid.dat)

# the commands to create the spatial objects:
require(sp)
jura.pred = prediction.dat
jura.val = validation.dat
jura.grid = juragrid.dat

jura.pred$Landuse = factor(prediction.dat$Landuse, labels=levels(juragrid.dat$Landuse))
jura.pred$Rock = factor(prediction.dat$Rock, labels=levels(juragrid.dat$Rock))
jura.val$Landuse = factor(validation.dat$Landuse, labels=levels(juragrid.dat$Landuse))
jura.val$Rock = factor(validation.dat$Rock, labels=levels(juragrid.dat$Rock))

coordinates(jura.pred) = ~Xloc+Yloc
coordinates(jura.val) = ~Xloc+Yloc
coordinates(jura.grid) = ~Xloc+Yloc
gridded(jura.grid) = TRUE