Compute LiDAR Metrics

Set filepaths

Code

PLOT_LAS_DIR = "data/plot_las_files"

LABELS_FPATH = "data/labels.csv"

METRICS_CSV_OUT_FPATH <- "data/lidar_metrics.csv"

RE_COMPUTE = FALSE

Load required R packages

Code

library(lidR)
library(here)
library(sf)
library(tidyverse)
library(purrr)
library(lidRmetrics)
library(Lmoments)

Load labels and plot point clouds

Code

labels_df <- read_csv(LABELS_FPATH)

# Read all las files
las_fpaths <- here(file.path(PLOT_LAS_DIR, paste0(labels_df$plot_id, ".las")))

Calculate LiDAR metrics using the lidR Metrics package

https://github.com/ptompalski/lidRmetrics

Code

calc_metrics <- function(las) {

  metrics <- lidRmetrics::metrics_set3(x = las@data$X, 
                                       y = las@data$Y, 
                                       z = las@data$Z, 
                                       i = las@data$Intensity,
                                       ReturnNumber = las@data$ReturnNumber,
                                       NumberOfReturns = las@data$NumberOfReturns)
  
  metrics <- unlist(metrics)

  metrics <- as.data.frame(t(metrics))

  stopifnot(ncol(metrics) == 108)

  if (!is.data.frame(metrics)) {
    stop("The output is not a data frame.")
  }

  return(metrics)
}

if(RE_COMPUTE){

  las_ls <- purrr::map(las_fpaths, readLAS, .progress = FALSE)

  metrics_df_ls <- purrr::map(las_ls, calc_metrics, .progress = TRUE)

  metrics_df <- dplyr::bind_rows(metrics_df_ls) %>%
                      # Drop any columns with NAs
                      dplyr::select(where(~!any(is.na(.))))

  # Add plot ID
  metrics_df$plot_id <- labels_df$plot_id

  # Export
  metrics_df %>% write_csv(METRICS_CSV_OUT_FPATH)

  metrics_df %>% head(3)
}