rasterToGrid {epm}

Convert raster to sf grid

Description

Convert a raster to sf polygons object, matching the attributes of the target object.

Usage

rasterToGrid(x, target, fun = "mean", crop = TRUE, na.rm = TRUE)

Arguments

x

rasterLayer or rasterStack or SpatRaster

target

epmGrid or sf object

fun

function for summarizing raster cells to polygons

crop

if TRUE, the raster will be cropped to the bounding box of the target

na.rm

determines how NA cells are summarized

Details

By default, raster cells that overlap with target grid cell polygons will be averaged. If target is a raster grid, then terra::resample is used.

Value

sf polygons object, or a list of such objects if input has multiple layers.

Author(s)

Pascal Title

Examples

library(terra)

# We have a terra grid object (for example, climate data read in as a raster)
# Here, we are just generating some random data for demo
env <- rast(vect(tamiasEPM[[1]]), resolution = 100000)
env[] <- sample(1:100, ncell(env), replace = TRUE)
plot(env)

# Now, if we are interested in doing analyses of environmental data in relation to 
# the epmGrid data we have, we want to convert the env data to the same grid structure
# where the cells align and where raster grid values are resampled and averaged.

newgrid <- rasterToGrid(env, target = tamiasEPM, fun = 'mean')
plot(newgrid)


# again but this time the input has multiple layers
env <- rast(vect(tamiasEPM[[1]]), resolution = 100000, nlyr = 3)
values(env[[1]]) <- sample(1:100, ncell(env), replace = TRUE)
values(env[[2]]) <- sample(1:200, ncell(env), replace = TRUE)
values(env[[3]]) <- sample(1:300, ncell(env), replace = TRUE)

newgrid <- rasterToGrid(env, target = tamiasEPM, fun = 'mean')