R Dataset / Package MASS / gilgais
On this R-data statistics page, you will find information about the gilgais data set which pertains to Line Transect of Soil in Gilgai Territory. The gilgais data set is found in the MASS R package. You can load the gilgais data set in R by issuing the following command at the console data("gilgais"). This will load the data into a variable called gilgais. If R says the gilgais data set is not found, you can try installing the package by issuing this command install.packages("MASS") and then attempt to reload the data with the library() command. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the gilgais R data set. The size of this file is about 12,113 bytes.
Line Transect of Soil in Gilgai Territory
Description
This dataset was collected on a line transect survey in gilgai territory in New South Wales, Australia. Gilgais are natural gentle depressions in otherwise flat land, and sometimes seem to be regularly distributed. The data collection was stimulated by the question: are these patterns reflected in soil properties? At each of 365 sampling locations on a linear grid of 4 meters spacing, samples were taken at depths 0-10 cm, 30-40 cm and 80-90 cm below the surface. pH, electrical conductivity and chloride content were measured on a 1:5 soil:water extract from each sample.
Usage
gilgais
Format
This data frame contains the following columns:
pH00
-
pH at depth 0–10 cm.
pH30
-
pH at depth 30–40 cm.
pH80
-
pH at depth 80–90 cm.
e00
-
electrical conductivity in mS/cm (0–10 cm).
e30
-
electrical conductivity in mS/cm (30–40 cm).
e80
-
electrical conductivity in mS/cm (80–90 cm).
c00
-
chloride content in ppm (0–10 cm).
c30
-
chloride content in ppm (30–40 cm).
c80
-
chloride content in ppm (80–90 cm).
Source
Webster, R. (1977) Spectral analysis of gilgai soil. Australian Journal of Soil Research 15, 191–204.
Laslett, G. M. (1989) Kriging and splines: An empirical comparison of their predictive performance in some applications (with discussion). Journal of the American Statistical Association 89, 319–409
References
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
Dataset imported from https://www.r-project.org.