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Prepare landscape rasters for focal statistics via Python

Source: R/python_focal_prep.R
python_focal_prep.Rd

Prepare for running focal statistics on a landscape raster via Python, to generate inputs for use with species distribution models.

Usage

python_focal_prep(
  landscape,
  SDM,
  pathout = NULL,
  landscape_name = NULL,
  suffix = NULL,
  mask = NULL,
  pixel_value = NULL,
  overwrite = FALSE
)

Arguments

landscape

SpatRaster created by terra::rast()

SDM

The name of intended species distribution model, for which landscape will be reclassified: "riparian", "waterbird_fall", "waterbird_win", or "tima"

pathout, landscape_name

Optional character strings defining the filepath (pathout/SDM/landscape_name) where output rasters should be written

suffix

Character string; custom suffix appended to layer names (optional unless mask is not NULL); see Details.

mask

Optional SpatRaster; see Details

pixel_value

Numeric value to replace cell values with (optional); default NULL

overwrite

Logical; passed to terra::writeRaster(); default FALSE

Value

SpatRaster, though primarily used to write layers to file for use with python_focal_run()

Details

This is a wrapper function that calls reclassify_landcover() to group and rename land covers in the provided landscape raster to match predictors in the intended species distribution model and split them into separate layers representing the presence (1) or absence (0) of each land cover class for use in calculating focal statistics. See documentation of that function for information about Warning messages.

Optionally, a custom suffix can be appended to the layer name and cell values representing land cover presence (1) can be replaced with a different pixel_value (e.g., the area of each pixel) as needed before writing the layers to pathout/SDM/landscape_name.

By providing a mask, this function can also use the land cover presence layers as a mask to extract the values of another layer (e.g., surface water data). To distinguish land cover presence from the values extracted from another layer, suffix is required to have two values. See examples.

See also

python_focal_run(), python_focal_finalize()

Examples

library(DeltaMultipleBenefits)
r <- terra::rast(matrix(sample(c(11,19,71,72,90), size = 100, replace = TRUE),
         ncol = 10, nrow = 10))

#return the presence of each land cover class
presence = suppressWarnings(python_focal_prep(landscape = r, SDM = 'riparian'))
#> AG RICE IDLE GRASSPAS URBAN SALIX MIXEDFOREST INTROSCRUB SALIXSHRUB MIXEDSHRUB PERM WOODLAND BARREN

#return the area of the pixel where each land cover class is present
#(useful for summing over moving windows)
area = suppressWarnings(python_focal_prep(landscape = r, SDM = 'waterbird_win', pixel_value = 0.09))
#> ww grain corn field row rice fal alf ip dryp dev wet duwet barren for

#mask another raster (e.g., surface water data) by where each land cover is present
w = r
terra::values(w) <- sample(c(0,1), size = 100, replace = TRUE)
#pfld = python_focal_prep(landscape = r, SDM = 'waterbird_fall', pixel_value = 0.09, mask = w)
#returns error: two values for suffix are required if mask is not `NULL`
pfld = suppressWarnings(
   python_focal_prep(
      landscape = r, SDM = 'waterbird_fall', pixel_value = 0.09,
       mask = w, suffix = c('_area', '_pfld')))
#> grain corn field row rice fal alf ip dryp dev wet duwet barren for