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)

Format

This data frame contains the following columns:

Xloc

see book

Yloc

see book

Landuse

see book and below

Rock

see book and below

Cd

see book

Co

see book

Cr

see book

Cu

see book

Ni

see book

Pb

see book

Zn

see book

Note

The points data sets were obtained from http://home.comcast.net/~goovaerts/book.html, the grid data were kindly provided by Pierre Goovaerts.

Rock Types: 1: Argovian, 2: Kimmeridgian, 3: Sequanian, 4: Portlandian, 5: Quaternary.

Land uses: 1: Forest, 2: Pasture (Weide(land), Wiese, Grasland), 3: Meadow (Wiese, Flur, Matte, Anger), 4: Tillage (Ackerland, bestelltes Land)

Points 22 and 100 in the validation set (validation.dat[c(22,100),]) seem not to lie exactly on the grid origininally intended, but are kept as such to be consistent with the book.

Author(s)

Data preparation by David Rossiter (rossiter@itc.nl) and Edzer Pebesma

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