CrownScorchTLS (version 0.1.1)

predict_scorch: Predict canopy scorch from `LAS` tree object following Cannon et al. 2025

Description

This function follows methods in Cannon et al. 2025 to predict crown scorch of a `LAS` object representing an individual tree collected using a RIEGL vz400i Terrestrial Lidar system. The function uses the 'relative reflectance' (in decibels) and predicts crown scorch using `randomForests` following Cannon et al. 2025

Usage

predict_scorch(las, model = NULL, plot = FALSE)

Value

predicted scorch as numeric vector

Arguments

las

`LAS` object from `lidR` package representing an individually segmented tree collected from RIEGL vz400i Terrestrial Lidar Scanner

model

`randomForests` model object containing histogram data generated from `get_histogram` function. if `model` is `NULL`, then default model from Cannon et al. 2025 is used. But custom model may be generated.

plot

Boolean indicating whether reflectance histogram should be plotted

Examples

library(lidR)
library(CrownScorchTLS)

#download external data from github repo
url <- paste0(
  "https://raw.githubusercontent.com/jbcannon/CrownScorchTLS-data/main/data/manual-clip-trees/",
  "M-04-15549_post.laz")
las_file = tempfile(fileext = paste0(".", tools::file_ext(url)))
download.file(url, las_file, mode = "wb", quiet = TRUE)
las <- readLAS(las_file)

# or load your own data
#las <- readLAS('C:/path/to/your/file.laz')

predict_scorch(las) #using default model from Cannon et al. 2025