Skip to contents

Compute areal means of raster data over polygons

Source: R/preprocessing_tools.R
areal_mean.Rd

Estimates mean values of raster cells for each polygon. Supports parallel processing, allowing each core to independently load and process raster layers from a NetCDF file. Used internally by pcp2swat_editor and tmp2swat_editor for SWAT input preparation.

Usage

areal_mean(
  grid,
  geom,
  start_date,
  time_step = "day",
  cores = 1,
  grid_file = NULL
)

Arguments

grid

A `SpatRaster` object for single-core processing.

geom

A set of polygons in `sf` format to perform the extraction.

start_date

The start date for the time series.

time_step

Time step between raster layers. Either 'day' or 'month'. Default is 'day'.

cores

Number of cores for parallel processing. Default is 1 (single-core).

grid_file

(Optional) Path to the NetCDF file for parallel processing.

Value

A data frame with the mean values extracted for each polygon and each raster layer.

See also

pcp2swat_editor, tmp2swat_editor, pcp2swat, tmp2swat

Other Preprocessing tools: pcp2swat(), pcp2swat_editor(), tmp2swat(), tmp2swat_editor()

Examples

# \donttest{
# Example with package NetCDF data
pr_nc <- system.file("extdata", "pr.nc", package = "hydroSWAT")
data(subs1, package = "hydroSWAT")
grid <- terra::rast(pr_nc)
result <- areal_mean(grid, subs1, "2010-01-01", time_step = "day")
# }

if (FALSE) { # \dontrun{
# Example with external NetCDF and shapefile
grid <- terra::rast("path_to_raster_file.nc")
geom <- sf::st_read("path_to_shapefile.shp")
result <- areal_mean(grid, geom, "1981-01-01", time_step = "day",
                     cores = 2, grid_file = "path_to_netCDF.nc")
} # }