csc_metrics | R Documentation |
csc_metrics
creates first-order canopy structural metrics that
do not require normalization
csc_metrics(df, filename, transect.length)
df |
data frame of uncorrected PCL data |
filename |
name of file currently being processed |
transect.length |
the length of the transect |
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 calculations.
slew of cover and sky fraction metrics
csc.metrics <- csc_metrics(pcl_adjusted, filename = "UVA", transect.length = 10)
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