Efficient Attribute-Weighted Rasterization Using Coverage Fraction

Rasterizes vector features to a raster grid defined by a planning unit (pus) layer, assigning values based on a given attribute and the actual coverage fraction of each feature over each raster cell. This method is optimized for speed and precision and is especially useful when features overlap or vary in size and shape.

Uso

exact_rasterise(
  features,
  attribute,
  iso3,
  pus,
  invert = FALSE,
  rescaled = TRUE,
  fun = mean,
  cores = 4
)

Argumentos

features

An sf or SpatVector object containing the vector features to rasterize.

attribute

Character. The column name in features to use as a weight for raster values.

iso3

Character. ISO3 country code, passed to make_normalised_raster().

pus

A SpatRaster object defining the resolution, extent, and CRS of the output raster.

invert

Logical. If TRUE, inverts the resulting values during normalization (default: FALSE).

rescaled

Logical. If TRUE, rescales the output to 0-1 using make_normalised_raster() (default: TRUE).

fun

Function. Aggregation function applied across overlapping rasterized features (default: mean).

cores

Integer. Number of CPU cores to use for multi-core processing (default: 4).

Valor

A SpatRaster object representing the attribute-weighted rasterization of the input features.

Detalhes

If multiple features are provided, each is rasterized independently and aggregated across the stack using the specified function (fun), typically sum, mean, or max.

Exemplos

if (FALSE) { # \dontrun{
# Rasterize polygons using a 'score' attribute
result <- exact_rasterise(features = my_polygons, attribute = "score", pus = my_raster, fun = sum)
} # }