csc_metrics creates first-order canopy structural metrics that
do not require normalization
Usage
csc_metrics(df, filename, transect.length)
Arguments
df
data frame of uncorrected PCL data
filename
name of file currently being processed
transect.length
the length of the transect
Value
slew of cover and sky fraction metrics
Details
The csc_metrics function processes uncorrected PCL data to
generate canopy structural complexity (CSC) metrics that do not
require normalization (i.e. correction for light saturation based on
Beer-Lambert Law). These metrics include: mean return height of raw data, sd
of raw canopy height returns, maximum measured canopy height, scan density (the
average no. of LiDAR returns per linear meter), and both openness and cover
fraction which are used for gap fraction calcuations.