csc_metrics: Cover and sky fraction estimates

In forestr: Ecosystem and Canopy Structural Complexity Metrics from LiDAR

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)

forestr documentation built on April 17, 2020, 1:26 a.m.