Data aggregation
The grainchanger package provides functionality for data aggregation to a grid via moving-window or direct methods.
Moving-window data aggregation
The moving-window data aggregation method smooths the surface using a specified function within a moving window of a specified size and shape prior to aggregation.
The moving window approach allows users to capture some information about landscape structure at the scale at which the process acts in the landscape.
The below example shows the moving-window data aggregation in action. It aggregates a categorical raster to a grid using Shannon evenness as the function calculated within a square moving window of 5 units. This value is included as a column on the grid sf object.
g_sf$mwda <- winmove_agg(
g = g_sf,
dat = cat_ls,
d = 5,
type = "rectangle",
fun = "shei",
lc_class = 0:3
)
#> Loading required package: raster
#> Loading required package: sp
show_landscape(cat_ls)
ggplot(g_sf) + geom_sf(aes(fill = mwda))
Direct data aggregation
The direct method simply aggregates to the grid using the specified function, essentially acting as a wrapper for the raster aggregate function.
The below example shows the direct data aggregation in action. It aggregates a continuous raster to a grid using the range as the function calculated for each cell of the larger grid. This value is included as a column on the grid sf object. var_range is an inbuilt function in the grainchanger package.
g_sf$range <- nomove_agg(
g = g_sf,
dat = cat_ls,
fun = "var_range")
show_landscape(cont_ls)
ggplot(g_sf) + geom_sf(aes(fill = range))
