USDA Textural Soil Classification

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Included in the next version (1.0.3.1) of ggtern, will be a new data set, taken from the USDA Textural Soil Classification[1] which we can use to reproduce the original diagram published by the United Stated Department of Agriculture.

Firstly let us load the packages and data:

# Load the required libraries
library(ggtern)
library(plyr)
library(grid)

# Load the Data. (Available in ggtern 1.0.3.0 next version)
data(USDA)

# Put tile labels at the midpoint of each tile.
USDA.LAB = ddply(USDA, 'Label', function(df) {
    apply(df[, 1:3], 2, mean)
})

# Tweak
USDA.LAB$Angle = 0
USDA.LAB$Angle[which(USDA.LAB$Label == 'Loamy Sand')] = -35

Reconstructing the USDA’s Original Plot

Now let us construct the plot from the prepared data

# Construct the plot.
ggplot(data = USDA, aes(y=Clay, x=Sand, z=Silt, 
                        color = Label, 
                        fill = Label)) + 
  coord_tern(L="x",T="y",R="z") + 
  geom_polygon(alpha = 0.75, size = 0.5, color = 'black') + 
  geom_text(data = USDA.LAB, 
            aes(label = Label, angle = Angle), 
            color = 'black', 
            size = 3.5) + 
  theme_rgbw() + 
  theme_showsecondary() + 
  theme_showarrows() + 
  custom_percent("Percent") + 
  theme(legend.justification = c(0, 1), 
        legend.position      = c(0, 1), 
        axis.tern.padding    = unit(0.15, 'npc')) + 
  labs(title = 'USDA Textural Classification Chart', 
       fill  = 'Textural Class', 
       color = 'Textural Class')

plot of chunk unnamed-chunk-2

Comparison to Existing Format

The above reproduction looks considerably better than the originally published format [1].

plot of original

References

[1] Unknown-Author, Soil Mechanics Level 1, Module 3, USDA Textural Classification Study Guide, United States Department of Agriculture, 1987.
[Bibtex]
@BOOK{usda,
title = {Soil Mechanics Level 1, Module 3, USDA Textural Classification Study
Guide},
publisher = {United States Department of Agriculture},
year = {1987},
author = {Unknown-Author},
owner = {Nick Hamilton},
timestamp = {20140116}
}

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