R: Soil data of North Bavaria, Germany

soil {RandomFields} | R Documentation

## Soil data of North Bavaria, Germany

### Description

Soil physical and chemical data collected on a field in the Weissenstaedter Becken, Germany

### Usage

    data(soil)

### Format

This data frame contains the following columns:

x.coord

  x coordinates given in cm

y.coord

  y coordinates given in cm

nr

  number of the samples, which were taken in this order

moisture

  moisture content [Kg/Kg * 100%]

NO3.N

  nitrate nitrogen [mg/Kg]

Total.N

  total nitrogen [mg/Kg]

NH4.N

  ammonium nitrogen [mg/Kg]

DOC

  dissolved organic carbon [mg/Kg]

N20N

  nitrous oxide [mg/Kg dried substance]

### Details

For technical reasons some of the data were obtained as differences of two measurements (which are not available anymore). Therefore, some of the data have negative values.

### Source

The data were collected by Wolfgang Falk, Soil Physics Group, University of Bayreuth, Germany.

### References

Falk, W. (2000) Kleinskalige raeumliche Variabilitaet von Lachgas und bodenchemischen Parameters [Small Scale Spatial Variability of Nitrous Oxide and Pedo-Chemical Parameters], Master thesis, University of Bayreuth, Germany.

### Examples

    RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
    ##                   RFoptions(seed=NA) to make them all random again

    ################################################################
    ## ##
    ## a geostatistical analysis that demonstrates ##
    ## features of the package `RandomFields' ##
    ## ##
    ################################################################

    data(soil)
    str(soil)
    soil <- RFspatialPointsDataFrame(
     coords = soil[ , c("x.coord", "y.coord")],
     data = soil[ , c("moisture", "NO3.N", "Total.N", "NH4.N", "DOC", "N20N")],
     RFparams=list(vdim=6, n=1)
    )
    data <- soil["moisture"]

    ## plot the data first
    colour <- rainbow(100)
    plot(data, col=colour)

    ## fit by eye
    gui.model <- RFgui(data)

    ## fit by ML
    model <- ~1 + RMwhittle(scale=NA, var=NA, nu=NA) + RMnugget(var=NA)
    (fit <- RFfit(model, data=data))
    plot(fit, method=c("ml", "plain", "sqrt.nr", "sd.inv"),
         model = gui.model, col=1:8)

    ## Kriging ...
    x <- seq(min(data@coords[, 1]), max(data@coords[, 1]), l=121)
    k <- RFinterpolate(fit, x=x, y=x, data=data)
    plot(x=k, col=colour)
    plot(x=k, y=data, col=colour)

    ## what is the probability that at no point of the
    ## grid given by x and y the moisture is greater than 24 percent?

    cs <- RFsimulate(model=fit, x=x, y=x, data=data, n=50)
    plot(cs, col=colour)
    plot(cs, y=data, col=colour)
    Print(mean(apply(as.array(cs) <= 24, 3, all))) ## about 40 percent ...

[Package RandomFields version 3.1.50 Index]