clean_raster: Applies thresholds and mask to a raster object

In lidaRtRee: Forest Analysis with Airborne Laser Scanning (LiDAR) Data

Applies thresholds and mask to a raster object

Description

Applies a lower and upper thresholds to the values of the input raster. If the mask input is provided, first all NA values in the raster are set to 0, then the raster in multiplied by the mask. Cells to be masked should therefore have a NA value in the mask raster object.

Usage

clean_raster(r, minmax = c(-Inf, +Inf), mask = NULL)

Arguments

r	raster object. RasterLayer and SpatRaster are supported.
minmax	vector of two numeric values. minimum and maximum thresholds to apply to 'r' values
mask	raster object. mask to be applied (multiplication with input raster 'r')

Value

a raster object

Examples

# load data
data(quatre_montagnes)
# build model
model_aba <- aba_build_model(quatre_montagnes$G_m2_ha, quatre_montagnes[, 9:76],
  transform = "boxcox"
)
# build example raster to apply model
quatre_montagnes$X <- rep(1:8, 12)
quatre_montagnes$Y <- rep(1:12, each = 8)
metrics_map <- terra::rast(quatre_montagnes[, c(2, 3, 9:76)], type = "xyz")
predict_map <- aba_predict(model_aba, metrics_map)
# create raster mask
mask <- predict_map
# set values to 1 or NA
terra::values(mask) <- rep(c(1, 1, NA), each = 32)
# apply thresholds and mask
predict_map_clean <- clean_raster(predict_map, c(40, 70), mask)

# plot maps
terra::plot(predict_map, main = "Predictions")
terra::plot(mask, main = "Mask", legend = FALSE)
terra::plot(predict_map_clean, main = "Cleaned predictions")

lidaRtRee documentation built on April 3, 2025, 10:29 p.m.