aqp (version 2.1.0)

soil_minerals: Munsell Colors of Common Soil Minerals

Description

Munsell colors for some common soil minerals.

Usage

data(soil_minerals)

Format

A data frame with 20 observations on the following 5 variables.

mineral

mineral name

color

Munsell color

hue

Munsell hue

value

Munsell value

chroma

Munsell chroma

Details

Soil color and other properties including texture, structure, and consistence are used to distinguish and identify soil horizons (layers) and to group soils according to the soil classification system called Soil Taxonomy. Color development and distribution of color within a soil profile are part of weathering. As rocks containing iron or manganese weather, the elements oxidize. Iron forms small crystals with a yellow or red color, organic matter decomposes into black humus, and manganese forms black mineral deposits. These pigments paint the soil (Michigan State Soil). Color is also affected by the environment: aerobic environments produce sweeping vistas of uniform or subtly changing color, and anaerobic (lacking oxygen), wet environments disrupt color flow with complex, often intriguing patterns and points of accent. With depth below the soil surface, colors usually become lighter, yellower, or redder.

References

1. Lynn, W.C. and Pearson, M.J., The Color of Soil, The Science Teacher, May 2000. 2. Schwertmann, U. 1993. Relations Between Iron Oxides, Soil Color, and Soil Formation. "Soil Color". SSSA Special Publication no. 31, pages 51--69.

Examples

if (FALSE) {

library(aqp)
library(ape)
library(cluster)
library(farver)

# load common soil mineral colors
data(soil_minerals)

# convert Munsell to R colors
soil_minerals$col <- munsell2rgb(
  soil_minerals$hue, 
  soil_minerals$value,
  soil_minerals$chroma
)

# make a grid for plotting
n <- ceiling(sqrt(nrow(soil_minerals)))

# read from top-left to bottom-right
g <- expand.grid(x=1:n, y=n:1)[1:nrow(soil_minerals),]

# convert Munsell -> sRGB -> LAB
col.rgb <- munsell2rgb(
  soil_minerals$hue,
  soil_minerals$value,
  soil_minerals$chroma,
  return_triplets = TRUE
)

# sRGB values expected to be in the range [0,255]
col.rgb <- col.rgb * 255

# convert from sRGB -> CIE LAB
col.lab <- convert_colour(
  col.rgb , from = 'rgb',
  to = 'lab', white_from = 'D65'
)

# keep track of soil mineral names
# in a way that will persist in a dist obj
row.names(col.lab) <- soil_minerals$mineral

# perceptual distance via CIE dE00
d <- compare_colour(
  from = col.lab,
  to = col.lab,
  from_space = 'lab',
  to_space = 'lab',
  white_from = 'D65',
  method = 'CIE2000'
)

# matrix -> dist
d <- as.dist(d)

# divisive hierarchical clustering of LAB coordinates
h <- as.hclust(diana(d))
p <- as.phylo(h)

# colors, in order based on clustering
# starting from top-left
min.cols <- rev(soil_minerals$col[h$order])

# mineral names, in order based on clustering
# starting from top-left
min.names <- rev(soil_minerals$mineral[h$order])

min.munsell <- rev(soil_minerals$color[h$order])

# plot grid of mineral names / colors
layout(matrix(c(1, 2), nrow = 1), widths = c(1.25, 1))

par(mar = c(1, 0, 0, 1))
plot(g$x, g$y, pch = 15, cex = 12, axes = FALSE, xlab = '', ylab = '',
     col = min.cols, 
     xlim = c(0.5, 5.5), ylim = c(1.5, 5.5)
)
text(g$x, g$y, min.names, adj = c(0.45, 5.5), cex = 0.75, font = 2)
text(g$x, g$y, min.munsell, col = invertLabelColor(min.cols), cex = 0.85, font = 2)

title(main = 'Common Soil Pigments', line = -1.75, cex.main = 2)
mtext('U. Schwertmann, 1993. SSSA Special Publication no. 31, pages 51--69', side = 1,
      cex = 0.75, line = -1.5)

# dendrogram + tip labels with mineral colors
plot(p, cex = 0.85, label.offset = 5, font = 1)
tiplabels(pch = 15, cex = 3, offset = 2, col = soil_minerals$col)

}