csc_metrics {forestr} | R Documentation |
Cover and sky fraction estimates
Description
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 |
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.
Value
slew of cover and sky fraction metrics
Examples
csc.metrics <- csc_metrics(pcl_adjusted, filename = "UVA", transect.length = 10)
[Package forestr version 2.0.2 Index]