aqp (version 1.42)

segment: Segmenting of Soil Horizon Data by Depth Interval

Description

This function adds depth interval ("segment") labels to soil horizon data associated with SoilProfileCollection and data.frame objects. Additional horizon records are inserted when a segment label does not overlap with a horizon boundary. See examples.

Usage

segment(object, intervals, trim = TRUE, hzdepcols = NULL)

Value

Either a SoilProfileCollection or data.frame with the original horizon data segmented by depth intervals. There are usually more records in the resulting object, one for each time a segment interval partially overlaps with a horizon. A new column called segment_id identifying the depth interval is added.

Arguments

object

either a SoilProfileCollection or data.frame

intervals

a vector of integers over which to slice the horizon data (e.g. c(25, 100) or 25:100)

trim

logical, when TRUE horizons in object are truncated to the min/max specified in intervals. When FALSE, those horizons overlapping an interval are marked as such. Care should be taken when specifying more than one depth interval and trim = FALSE.

hzdepcols

a character vector of length 2 specifying the names of the horizon depths (e.g. c("hzdept", "hzdepb")), only necessary if object is a data.frame.

Author

Stephen Roecker

Details

This function adds segment labels to soil horizon data according to intgervals (e.g. c(25, 100) or 25:100). Compared to slice, slab, and glom, segment performs no aggregation or resampling of the source data, rather, labels are added to horizon records for subsequent aggregation. This makes it possible to process a very large number of records outside of the constraints associated with e.g. slice or slab.

Examples

# example data
data(sp1)

# upgrade to SPC
depths(sp1) <- id ~ top + bottom

# segment and trim
z <- segment(sp1, intervals = c(0, 10, 20, 30), trim = TRUE)

# display segment labels
# note that there are new horizon boundaries at segments
par(mar = c(0, 0, 3, 1))
plotSPC(z, color = 'segment_id', width = 0.3)

# highlight new horizon records
par(mar = c(0, 0, 2, 1))
plotSPC(z, color = NA, default.color = NA, width = 0.3, lwd = 1)
plotSPC(sp1, color = NA, default.color = NA, 
width = 0.3, lwd = 3, add = TRUE, name = NA, print.id = FALSE)
legend('top', horiz = TRUE, 
legend = c('original', 'segmented'), 
lwd = c(1, 3), cex = 0.85, bty = 'n')

# \donttest{
# same results as slab()
# 10 random profiles
s <- lapply(1:10, random_profile, n_prop = 1, SPC = TRUE, method = 'random_walk')
s <- combine(s)

a.slab <- slab(s, fm = ~ p1, slab.structure = c(0, 10, 20, 30), slab.fun = mean, na.rm = TRUE)

z <- segment(s, intervals = c(0, 10, 20, 30), trim = TRUE)
z <- horizons(z)
z$thick <- z$bottom - z$top

a.segment <- sapply(split(z, z$segment_id), function(i) {
  weighted.mean(i$p1, i$thick)
})


res <- data.frame(
  slab = a.slab$value,
  segment = a.segment,
  diff = a.slab$value - a.segment
)

print(res)
res$diff < 0.001
# }


data(sp5)

# segment by upper 25-cm
test1 <- segment(sp5, intervals = c(0, 100))
print(test1)
nrow(test1)
print(object.size(test1), units = "Mb")

# segment by 1-cm increments
test2 <- segment(sp5, intervals = 0:100)
print(test2)
nrow(test2)
print(object.size(test2), units = "Mb")


# segment and aggregate
test3 <- segment(horizons(sp5), 
                 intervals = c(0, 5, 15, 30, 60, 100, 200), 
                 hzdepcols = c("top", "bottom")
)
test3$hzthk <- test3$bottom - test3$top
test3_agg <- by(test3, test3$segment_id, function(x) {
  data.frame(
    hzID = x$hzID[1],
    segment_id = x$segment_id[1],
    average = weighted.mean(x$clay, w = x$hzthk)
  )
})
test3_agg <- do.call("rbind", test3_agg)

head(test3_agg)