Summarize and replace values in predictors with an aggregation

This function supports the aggregation and specification of values inside a predictor set. Concretely, all predictor values underneath each zonal polygon (or id) are summarized through a function and then set as new values to the predictor set.

Usage

predictor_summarize_zones(
  env,
  layer,
  fun = "mean",
  target_layer = NULL,
  value = NULL
)

Arguments

env

A SpatRaster object with the predictors.

layer

Either a SpatRaster or a sf object.

fun

A custom function or character. A range of methods are supported by default such as "mean", "sum", "min" or "max" (Default: "mean").

target_layer

(Optional) SpatRaster object with categorical zones for which the summarized value is to be set.

value

(Optional) numeric value instead of the layer.

Value

A SpatRaster object with the same number of layers as the input.

Details

Potential uses of this function include for example the summary of values within a set of regions (such as countries or super cells). Optional target layers (for example another zone) and values can be defined.

Examples

if (FALSE) { # \dontrun{
# Load example data
background <- terra::rast(system.file('extdata/europegrid_50km.tif',
package='ibis.iSDM',mustWork = TRUE))

co <- terra::rast(system.file('extdata/countries.tif',
package='ibis.iSDM',mustWork = TRUE))

# Get the UK
co <- co=="United Kingdom"
co[co==0] <- NA

# Get list of test predictors
ll <- list.files(system.file('extdata/predictors/', package = 'ibis.iSDM',
mustWork = TRUE),full.names = TRUE)
# Load them as rasters
env <- terra::rast(ll[3])

# Load the layer
env_r <- predictor_summarize_zones(env, layer = co, fun = 'mean')
terra::plot(c(env, env_r), main = c("original", "aggregated"))
} # }