divraster (version 1.2.3)

rast.by.polys: Summarise raster values by polygons

Description

Extracts values from a SpatRaster for each polygon in a SpatVector and returns a data frame that combines polygon identifiers with user-defined summary statistics of the raster values.

Usage

rast.by.polys(
  x,
  polygons,
  id_col = NULL,
  fun = function(v, ...) mean(v, na.rm = TRUE),
  na.rm = TRUE
)

Value

A data.frame with one row per polygon. If id_col is not NULL, the first column is the specified identifier; otherwise, all attribute columns from polygons are included. Additional columns contain the summary statistics returned by fun for each raster layer.

Arguments

x

A SpatRaster object containing one or more layers.

polygons

A SpatVector with polygon geometries used to summarise raster values.

id_col

Optional character string giving the name of a column in polygons to be used as an identifier (for example, "PA_ID"). If NULL (default), all non-geometry attributes from polygons are joined to the summary table.

fun

A function applied to the vector of raster values extracted for each polygon. The function must return a named vector. It should accept ... so that arguments such as na.rm = TRUE can be passed through. The default is function(v, ...) mean(v, na.rm = TRUE).

na.rm

Logical; if TRUE, missing values are removed before applying fun. Passed to fun via ....

Details

This function is a convenience wrapper around terra::extract(), combining extraction, summarisation and binding of polygon attributes into a single step. It supports multilayer rasters; in that case the summary statistics are returned for each layer.

Examples

# \donttest{
library(terra)

# Example SpatRaster and SpatVector
r <- rast(system.file("ex/elev.tif", package = "terra"))
v <- as.polygons(r > 500, dissolve = TRUE)
v$PA_ID <- paste0("PA_", seq_len(nrow(v)))

# Mean elevation per polygon
pa_stats <- rast.by.polys(
  x        = r,
  polygons = v,
  id_col   = "PA_ID"
)

# Multiple statistics per polygon
pa_stats_multi <- rast.by.polys(
  x        = r,
  polygons = v,
  id_col   = "PA_ID",
  fun      = function(v, ...) c(
    mean = mean(v, ...),
    min  = min(v, ...),
    max  = max(v, ...)
  ),
  na.rm    = TRUE
)
# }