Note

All of these functions will be simplified / documented in the near future, stay tuned.

Introduction

Pending.

TODO

Examples

Source colors are in sRGB (D65) colorspace, as converted from Munsell notation using aqp::munsell2rgb().

Basic Idea

Trivial example using some of the aqp built-in data.

library(aqp)
library(farver)
library(cluster)
library(ape)
library(colorspace)
library(soilDB)
library(sharpshootR)

# example data
data(sp5)

# semi-random subset
set.seed(10101)
idx <- sample(length(sp5), size = 15, replace = FALSE)

# truncate to 150cm for simplicity
x <- trunc(sp5[idx, ], 0, 150)

# quick check
par(mar = c(0, 0, 0, 1))
plotSPC(x, width = 0.35)

# convert HEX color notation -> sRGB [0,1]
rgb.data <- t(col2rgb(x$soil_color)) / 255

# copy to horizon level attributes of SPC
x$r <- rgb.data[, 1]
x$g <- rgb.data[, 2]
x$b <- rgb.data[, 3]

# develop color signature
pig <- soilColorSignature(x, method = 'depthSlices', RescaleLightnessBy = 5)
knitr::kable(pig, digits = 3, row.names = FALSE)
soil A.0.1 A.0.5 A.0.9 B.0.1 B.0.5 B.0.9 L.0.1 L.0.5 L.0.9
soil100 5.447 8.769 9.510 15.982 22.157 21.267 6.177 10.191 12.184
soil102 7.275 13.824 11.642 8.138 16.434 20.356 6.235 10.186 8.212
soil107 4.794 7.275 7.049 9.798 8.138 21.026 6.296 6.235 6.274
soil155 7.275 7.275 7.275 8.138 8.138 8.138 6.235 6.235 6.235
soil156 2.037 2.037 13.220 5.446 5.446 19.206 6.148 6.148 10.165
soil167 4.794 4.794 15.597 9.798 9.798 17.731 6.296 6.296 8.250
soil168 7.275 7.275 9.453 8.138 8.138 5.188 6.235 6.235 16.139
soil189 7.275 12.172 16.673 8.138 19.396 31.254 6.235 12.308 10.235
soil226 2.037 2.037 2.037 5.446 5.446 5.446 6.148 6.148 6.148
soil332 8.630 7.275 1.346 8.687 8.138 6.864 6.306 6.235 8.321
soil340 7.275 11.642 13.220 8.138 20.356 19.206 6.235 8.212 10.165
soil341 7.275 8.826 8.558 8.138 14.803 13.285 6.235 8.294 6.323
soil40 2.037 4.794 5.447 5.446 9.798 15.982 6.148 6.296 6.177
soil419 7.275 19.442 5.293 8.138 26.882 24.202 6.235 8.259 16.177
soil79 7.275 6.103 8.096 8.138 7.305 8.186 6.235 4.293 8.229

Plot results as dendrogram.

# copy ID to rownames
row.names(pig) <- pig[, 1]

# euclidean distance, leaving out the ID
d <- daisy(pig[, -1], stand = FALSE, metric = 'euclidean')
dd <- diana(d)

plotProfileDendrogram(x, clust = dd, scaling.factor = 0.33, y.offset = 4, width = 0.35)

Colors from Official Series Descriptions

s.list <- c('amador', 'redding', 'pentz', 'willows', 'pardee', 'yolo', 'hanford', 'cecil', 'sycamore', 'KLAMATH', 'MOGLIA', 'vleck', 'drummer', 'CANEYHEAD', 'musick', 'sierra', 'HAYNER', 'zook', 'argonaut', 'PALAU')

# get these soil series
s <- fetchOSD(s.list)

# manually convert Munsell -> sRGB
rgb.data <- munsell2rgb(s$hue, s$value, s$chroma, return_triplets = TRUE)
s$r <- rgb.data$r
s$g <- rgb.data$g
s$b <- rgb.data$b

# check
par(mar=c(0, 0, 0, 1))
plotSPC(s, name.style = 'center-center', width = 0.33)

Look at full range of OSD colors in this set.

Colors, arranged by ΔE00.

previewColors(s$soil_color)

rgb.colors <- munsell2rgb(s$hue, s$value, s$chroma, return_triplets = TRUE)
lab.colors <- as(sRGB(rgb.colors[['r']], rgb.colors[['g']], rgb.colors[['b']]), 'LAB')@coords
cols <- cbind(rgb.colors, lab.colors)
cols <- na.omit(cols)
cols <- as.data.frame(cols)
pairs(~ L + A + B, data=cols, pch=16, cex=2, col=rgb(cols$r, cols$g, cols$b))

Soil Color Signature by “Pigment Proportions”

Compute proportions of white, red, green, yellow, and blue “pigments” based on the CIE LAB representation of soil colors distributed over horizons, weighted by horizon thickness. Pigment proportions are used so that shallow soils can be compared with deep soils. Each row is an observation, columns describe the multivariate soil color signature.

# what is appropriate rescaling of L?
pig <- soilColorSignature(s, RescaleLightnessBy = 5, method = 'colorBucket')

knitr::kable(head(pig), digits = 3, row.names = FALSE)
id .white.pigment .red.pigment .green.pigment .yellow.pigment .blue.pigment
AMADOR 0.311 0.124 0.000 0.564 0.000
ARGONAUT 0.159 0.328 0.000 0.513 0.000
CANEYHEAD 0.560 0.061 0.050 0.330 0.000
CECIL 0.120 0.413 0.000 0.467 0.000
DRUMMER 0.473 0.103 0.004 0.417 0.003
HANFORD 0.244 0.162 0.000 0.594 0.000 
# move row names over for distance matrix
row.names(pig) <- pig[, 1]
d <- daisy(pig[, -1], stand = FALSE)
dd.colorBucket <- diana(d)


par(mar=c(0,0,1,1))
plotProfileDendrogram(s, dd.colorBucket, dend.y.scale = 1.18, scaling.factor = 0.0037, y.offset = 0.06, width = 0.33, cex.names = 0.45, shrink = TRUE, name.style = 'center-center', max.depth = 210)