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Filter point clouds

Source: R/catalog_filter.R
catalog_filter.Rd

This function filters point clouds to remove or classify noise and outlier points

Usage

catalog_filter(
  lascatalog,
  filter_noise = TRUE,
  algorithm_noise = ivf(5, 2),
  filter_heights = TRUE,
  bins_height = c(300, 1600),
  filter_mode = "remove",
  output_path,
  filename_convention = "{ORIGINALFILENAME}",
  parallel = FALSE,
  n_cores = 2
)

Arguments

lascatalog

object of class lascatalog.

filter_noise

logical of length 1. If TRUE filters noise based on the algorithm defined in algorithm_noise

algorithm_noise

An algorithm used for filtering noise, see lidR::classify_noise(). Defaults to ivf(5,2)

filter_heights

logical of length 1. If TRUE filters outliers based on upper and lower heights defined by bins_height

bins_height

numeric list of length 2, defines the lower and upper heights to be kept in the dataset

filter_mode

character; either "remove" or "classify". When "remove": points filtered are removed from tha dataset, when "classify" points filtered are classified as noise.

output_path

character path to the folder where the new files should be exported to

filename_convention

character defining the filenames of the generated laz files following lidR basics. Defaults to the original filename

parallel

logical of length 1. Should the computation be split over several cores? Defaults to FALSE.

n_cores

numeric of length 1. If parall = TRUE, on how many cores should the computations be run on? Defaults to the value registered in options("cores")[[1]], or, if this is not available, to parallel::detectCores()).

Value

lascatalog

Examples