aqp: harden.melanization – R documentation

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harden.melanization

Harden (1982) Melanization

Description

Calculate Melanization component of Profile Development Index after Harden (1982) "A quantitative index of soil development from field descriptions: Examples from a chronosequence in central California". Accepts vectorized inputs for value and reference value to produce vector output. A convenient use case would be to apply this on a profile-specific basis, where the value_ref has a single value, and value is a vector of length equal to the number of horizons within the upper 100 cm.

Usage

harden.melanization(value, value_ref)

Arguments

`value`	numeric vector containing Munsell values
`value_ref`	A numeric vector containingMunsell value(s) for reference material

Details

In Harden (1982), melanization is calculated relative to a reference parent material for all horizons within 100cm of the soil surface. In addition, several other non-color components are normalized relative to a maximum value and summed to obtain the overall Profile Development Index.

Value

A numeric vector reflecting horizon darkening relative to a reference (e.g. parent) material.

Author(s)

Andrew G. Brown.

References

Harden, J.W. (1982) A quantitative index of soil development from field descriptions: Examples from a chronosequence in central California. Geoderma. 28(1) 1-28. doi: 10.1016/0016-7061(82)90037-4

Examples

library(aqp)
data("jacobs2000", package="aqp")

# LEFT JOIN hue, value, chroma matrix color columns
horizons(jacobs2000) <- cbind(horizons(jacobs2000)[,c(idname(jacobs2000), hzidname(jacobs2000))],
                              parseMunsell(jacobs2000$matrix_color_munsell, convertColors = FALSE))

# calculate a mixed 150-200cm color ~"parent material"

jacobs2000$c_horizon_color <- profileApply(jacobs2000, function(p) {

  # and derive the parent material from the 150-200cm interval
  p150_200 <- glom(p, 150, 200, truncate = TRUE)
  p150_200$thickness <- p150_200$bottom - p150_200$top

  # mix colors
  clrs <- na.omit(horizons(p150_200)[,c('matrix_color_munsell','thickness')])
  mixMunsell(clrs$matrix_color_munsell, w = clrs$thickness)$munsell

})

# segment profile into 1cm slices (for proper depth weighting)
jacobs2000$melan <- profileApply(jacobs2000, function(p) {

  # sum the melanization index over the 0-100cm interval
  p0_100 <- segment(p, 0:100)

  ccol <- parseMunsell(p$c_horizon_color, convertColors = FALSE)

  sum(harden.melanization(
    value = as.numeric(p0_100$value),
    value_ref = as.numeric(ccol$value)), na.rm = TRUE)

})

jacobs2000$melanorder <- order(jacobs2000$melan)

# Plot in order of increasing Melanization index

plotSPC(jacobs2000, axis.line.offset = -1,
        color = "matrix_color",
        label = "melan",
        plot.order = jacobs2000$melanorder)

abline(h = c(0,100,150,200), lty = 2)

# Add [estimated] parent material color swatches
lapply(seq_along(jacobs2000$c_horizon_color), function(i) {
  rect(i - 0.15, 250, i + 0.15, 225,
       col = parseMunsell(jacobs2000$c_horizon_color[jacobs2000$melanorder[i]]))
})

aqp

Algorithms for Quantitative Pedology

v1.29

GPL (>= 3)

Authors

Dylan Beaudette [aut, cre], Pierre Roudier [aut, ctb], Andrew Brown [aut, ctb]

Initial release

2021-04-05