aggregateColor: Summarize Soil Colors

In aqp: Algorithms for Quantitative Pedology

Description

Summarize soil color data, weighted by occurrence and horizon thickness.

Usage

aggregateColor(x, groups = "genhz", col = "soil_color")

Arguments

x	a SoilProfileCollection object
groups	the name of a horizon or site attribute used to group horizons, see examples
col	the name of a horizon-level attribute with soil color specified in hexadecimal (i.e. "#rrggbb")

Details

Weights are computed by: w_i = sqrt(sum(thickness_i)) * n_i where w_i is the weight associated with color i, thickness_i is the total thickness of all horizons associated with the color i, and n_i is the number of horizons associated with color i. Weights are computed within groups specified by groups.

Value

A list with the following components:

scaled.data	a list of colors and associated weights, one item for each generalized horizon label with at least one color specified in the source data
aggregate.data	a data.frame of weighted-mean colors, one row for each generalized horizon label with at least one color specified in the source data

Author(s)

D.E. Beaudette

See Also

generalize.hz

Examples

# load some example data
data(sp1, package='aqp')

# upgrade to SoilProfileCollection and convert Munsell colors
sp1$soil_color <- with(sp1, munsell2rgb(hue, value, chroma))
depths(sp1) <- id ~ top + bottom
site(sp1) <- ~ group

# generalize horizon names
n <- c('O', 'A', 'B', 'C')
p <- c('O', 'A', 'B', 'C')
sp1$genhz <- generalize.hz(sp1$name, n, p)

# aggregate colors over horizon-level attribute: 'genhz'
a <- aggregateColor(sp1, 'genhz')

# aggregate colors over site-level attribute: 'group'
a <- aggregateColor(sp1, 'group')

# aggregate colors over depth-slices
s <- slice(sp1, c(5, 10, 15, 25, 50, 100, 150) ~ soil_color)
s$slice <- paste0(s$top, ' cm')
a <- aggregateColor(s, 'slice')

## Not run: 
# optionally plot with helper function
if(require(sharpshootR))
  aggregateColorPlot(a)

## End(Not run)

# a more interesting example
## Not run: 
data(loafercreek, package = 'soilDB')

# generalize horizon names using REGEX rules
n <- c('Oi', 'A', 'BA','Bt1','Bt2','Bt3','Cr','R')
p <- c('O', '^A$|Ad|Ap|AB','BA$|Bw', 
'Bt1$|^B$','^Bt$|^Bt2$','^Bt3|^Bt4|CBt$|BCt$|2Bt|2CB$|^C$','Cr','R')
loafercreek$genhz <- generalize.hz(loafercreek$hzname, n, p)

# remove non-matching generalized horizon names
loafercreek$genhz[loafercreek$genhz == 'not-used'] <- NA
loafercreek$genhz <- factor(loafercreek$genhz)

a <- aggregateColor(loafercreek, 'genhz')

# plot results with helper function
par(mar=c(1,4,4,1))
aggregateColorPlot(a, print.n.hz = TRUE)

# inspect aggregate data
a$aggregate.data

## End(Not run)

Example output

This is aqp 1.10
Loading required package: sharpshootR
  genhz munsell.hue munsell.value munsell.chroma munsell.sigma     col
1     A         5YR             3              4   0.029771789 #694628
2    BA       2.5YR             3              4   0.071290531 #734C2D
3   Bt1       7.5YR             4              5   0.041072698 #7B512F
4   Bt2       7.5YR             4              5   0.016509536 #855532
5   Bt3       2.5YR             4              6   0.048991327 #8F5E39
6    Cr        10YR             5              5   0.001899109 #997544
        red     green      blue  n
1 0.4109907 0.2727869 0.1579144 20
2 0.4502043 0.2976214 0.1781636 11
3 0.4836490 0.3167008 0.1842734 20
4 0.5213726 0.3341825 0.1945891 23
5 0.5611859 0.3687704 0.2223375 17
6 0.6000000 0.4588235 0.2666667  1

aqp documentation built on May 2, 2019, 4:51 p.m.