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, as well as geographic
coordinates. The examples below show how to transform these into
spatial (sp) objects in a local coordinate system and in geographic
coordinates, and how to transform to metric coordinate reference
systems.
Usage
data(jura)
Format
The data.frames prediction.dat and validation.dat contain the following fields:
Xloc
X coordinate, local grid km
Yloc
Y coordinate, local grid km
Landuse
see book and below
Rock
see book and below
Cd
mg cadmium kg^-1 topsoil
Co
mg cobalt kg^-1 topsoil
Cr
mg chromium kg^-1 topsoil
Cu
mg copper kg^-1 topsoil
Ni
mg nickel kg^-1 topsoil
Pb
mg lead kg^-1 topsoil
Zn
mg zinc kg^-1 topsoil
The data.frame juragrid.dat only has the first four fields.
In addition the data.frames jura.pred, jura.val and jura.grid also
have inserted third and fourth fields giving geographic coordinates:
long
Longitude, WGS84 datum
lat
Latitude, WGS84 datum
Note
The points data sets were obtained from
http://home.comcast.net/~pgoovaerts/book.html, which seems to be
no longer available; the grid data were kindly provided by Pierre
Goovaerts.
The following codes were used to convert prediction.dat
and validation.dat to jura.pred and jura.val
(see examples below):
Points 22 and 100 in the validation set
(validation.dat[c(22,100),]) seem not to lie exactly on the
grid originally intended, but are kept as such to be consistent with
the book.
Georeferencing was based on two control points in the Swiss grid system
shown as Figure 1 of Atteia et al. (see above) and further points digitized
on the tentatively georeferenced scanned map. RMSE 2.4 m. Location of points
in the field was less precise.
Author(s)
Data preparation by David Rossiter (dgr2@cornell.edu)
and Edzer Pebesma; georeferencing by David Rossiter
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 following commands were used to create objects with factors instead
# of the integer codes for Landuse and Rock:
## Not run:
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))
## End(Not run)
# the following commands convert data.frame objects into spatial (sp) objects
# in the local grid:
require(sp)
coordinates(jura.pred) = ~Xloc+Yloc
coordinates(jura.val) = ~Xloc+Yloc
coordinates(jura.grid) = ~Xloc+Yloc
gridded(jura.grid) = TRUE
# the following commands convert the data.frame objects into spatial (sp) objects
# in WGS84 geographic coordinates
# example is given only for jura.pred, do the same for jura.val and jura.grid
# EPSG codes can be found by searching make_EPSG()
jura.pred <- as.data.frame(jura.pred)
coordinates(jura.pred) = ~ long + lat
proj4string(jura.pred) = CRS("+init=epsg:4326")
# display in Google Earth
if (require(maptools)) {
kmlPoints(jura.pred,
kmlfile="JuraPred.kml",
kmlname="Jura Prediction Points",name=row.names(jura.pred@data),
description=paste(jura.pred$Landuse, jura.pred$Rock, sep="/"))
if (require(rgdal)) {
# transform to UTM 32N
jura.pred.utm32n = spTransform(jura.pred,
CRS("+init=epsg:32632"))
coordnames(jura.pred.utm32n) = c("E","N")
# transform to Swiss grid system CH1903 / LV03
jura.pred.ch = spTransform(jura.pred,
CRS("+init=epsg:21781"))
coordnames(jura.pred.ch) = c("X","Y")
}
}