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Overview

PC2Products

PC2Products processes LiDAR point clouds with R and lidR, called from Python through rpy2. Every tool can be run from the BERA Tools GUI, from the bt command, or from Python.

Key Features

  • Dataset summary and recommended raster cell size from point density
  • Ground classification with the Cloth Simulation Filter (CSF)
  • DTM (TIN, IDW, kriging), height normalization, and CHM/DSM (TIN, pit-free)
  • Hummock/hollow micro-topography mapping
  • Surface water mapping from an orthomosaic, and depth to water by kriging
  • Seismic line disturbance statistics, adapted from Chan, Dabros & McDermid (2026)
  • Tiled, parallel processing, with merged mosaics of the outputs

Data Formats & Conventions

  • Point clouds: LAS / LAZ, read from a folder as a lidR LAScatalog
  • Raster: GeoTIFF
  • Vector: GeoPackage, given as file.gpkg|layer
  • Use a projected coordinate system in metres

PC2Products Tools

Tool bt subcommand Details
LiDAR data info las_info Prints the CRS, extent, density and normalization status of a dataset.
Raster Cell size from LiDAR data cellsize Recommends a raster cell size from the point density.
Ground Classify Using CSF gnd_csf Classifies ground points with the Cloth Simulation Filter.
Generate DTM from LiDAR Data dtm Builds a bare-earth DTM with TIN, IDW or kriging.
Normalize LiDAR Data normalize Subtracts the terrain so that Z is height above ground.
Generate CHM or DSM from LiDAR Data chm_dsm Builds a CHM from normalized data, or a DSM from the original data.
Detect Hummock and Hollow from LiDAR Data hh Maps hummocks, hollows and lawns relative to a smoothed terrain.
Surface Water Mapping surface_water Classifies surface water from a true-colour orthomosaic.
Depth-to-Water from Surface Water dtw Kriges a water table from surface water and computes depth to water.
Seismic Line Disturbance Analysis line_analysis Compares seismic line segments with the surrounding peatland by disturbance class.