Direct data aggregation

Source: R/nomove_agg.R

Calculate the value for a given function for each cell in a larger resolution grid.

nomove_agg(coarse_dat, fine_dat, agg_fun, is_grid = TRUE, quiet = FALSE, ...)

Arguments

coarse_dat

sf, Raster* or Spatial* object. The coarse grain data (response data) across which to calculate the aggregated function
fine_dat

Raster* object. Raster* object. The fine grain data (predictor / covariate data) to aggregate
agg_fun

function The function to apply. The function fun should take multiple numbers, and return a single number. For example mean, modal, min or max. It should also accept a na.rm argument (or ignore it, e.g. as one of the 'dots' arguments. For example, length will fail, but function(x, ...)na.omit(length(x)) works. See Details
is_grid

logical. Use TRUE (default) if g contains only rectangular cells (i.e. a grid). If g is any other polygon file, this should be set to false
quiet

logical. If FALSE (default) and is_grid == TRUE the user gets a warning that the aggregation assumes all cells are rectangular
...

further arguments passed to or from other methods

Value

Raster (if input is Raster) or numeric vector (if input is sp or sf object) containing values calculated for each coarser cell

Details

grainchanger has several built-in functions. Functions currently included are:

  • shdi - Shannon diversity, requires the additional argument lc_class (vector or scalar)

  • shei - Shannon evenness, requires the additional argument lc_class (vector or scalar)

  • prop - Proportion, requires the additional argument lc_class (scalar)

  • var_range - Range (max - min)

Note that nomove_agg can be run in parallel using plan(multiprocess) from the future package.

Examples

# load required data
data(g_sf)
data(cont_ls)
data(cat_ls)

# aggregate using mean
d <- nomove_agg(g_sf, cont_ls, mean)
#> aggregation assumes all cells are rectangular
#> ● set `is_grid = FALSE` if coarse_dat is not a grid

# aggregate using Shannon evenness
d <- nomove_agg(g_sf, cont_ls, shei, lc_class = 1:4)
#> aggregation assumes all cells are rectangular
#> ● set `is_grid = FALSE` if coarse_dat is not a grid