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Tip revision: 1402a3d4a695b8bf8dc225e4d787d46a21fb6ff6 authored by Edzer Pebesma on 20 September 2010, 07:41:03 UTC
version 0.9-71
Tip revision: 1402a3d
jura.Rd
% $Id: jura.Rd,v 1.3 2007-03-08 09:35:49 edzer Exp $
\name{jura}
\alias{jura}
\alias{prediction.dat}
\alias{validation.dat}
\alias{transect.dat}
\alias{juragrid.dat}
\alias{jura.grid}
\alias{jura.pred}
\alias{jura.val}
\title{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.
}
\format{
  This data frame contains the following columns:
  \describe{
	\item{Xloc}{ see book }
	\item{Yloc}{ see book }
	\item{Landuse}{ see book and below }
	\item{Rock}{ see book and below }
	\item{Cd}{ see book }
	\item{Co}{ see book }
	\item{Cr}{ see book }
	\item{Cu}{ see book }
	\item{Ni}{ see book }
	\item{Pb}{ see book }
	\item{Zn}{ see book }
  }
}
\usage{
data(jura)
}
\author{ 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

}
\note{
The points data sets were obtained from \url{
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
(\code{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.
}

\keyword{datasets}
\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
}
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