process_tls {forestr} | R Documentation |
Process single PCL transects.
Description
process_tls
imports and processes a slice from a voxelated TLS scan.
Usage
process_tls(f, slice, pavd = FALSE, hist = FALSE, save_output = TRUE)
Arguments
f |
the name of the filename to input <character> or a data frame <data frame>. |
slice |
the number of the transect to use from xyz tls data |
pavd |
logical input to include Plant Area Volume Density Plot from |
hist |
logical input to include histogram of VAI with PAVD plot, if TRUE it is included, if FALSE, it is not. |
save_output |
needs to be set to true, or else you are just going to get a lot of data on the screen |
Details
This function takes as input a four column .CSV file or data frame of x, y, z, and VAI (Vegetation Area Index) derived from 3-D (TLS) LiDAR data. Currently, this function only analyzes a single slice from the inputed TLS data set. VAI is calculated externally by the user using user-determined methodology.
The process_tls
function will write multiple output files to disk in an (output)
directory that process_tls
creates within the work directing. These files include:
1. an output variables file that contains a list of CSC variables and is
written by the subfunction write_pcl_to_csv
2. a summary matrix, that includes detailed information on each vertical column of Lidar data
written by the subfunction write_summary_matrix_to_csv
3. a hit matrix, which is a matrix of VAI at each x and z position, written by the
subfunction write_hit_matrix_to_pcl
4. a hit grid, which is a graphical representation of VAI along the x and z coordinate space.
5. optionally, plant area/volume density profiles can be created by including
pavd = TRUE
that include an additional histogram with the optional hist = TRUE
in the
process_pcl
call.
Value
writes the hit matrix, summary matrix, and output variables to csv in an output folder, along with hit grid plot
See Also
Examples
# with designated file
uva.tls<- system.file("extdata", "UVAX_A4_01_tls.csv", package = "forestr")
process_tls(uva.tls, slice = 5, pavd = FALSE, hist = FALSE, save_output = FALSE)