rasterToGrid {epm} | R Documentation |
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 |
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')
[Package epm version 1.1.2 Index]