winmove_agg: Moving-window data aggregation

In grainchanger: Moving-Window and Direct Data Aggregation

Description

Calculate the mean moving window value for a given radius, shape and function for each cell in a larger resolution grid.

Usage

winmove_agg(
  coarse_dat,
  fine_dat,
  d,
  type = c("circle", "rectangle"),
  win_fun,
  agg_fun = mean,
  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 moving window function
fine_dat	Raster* object. The fine grain data (predictor / covariate data) to aggregate
d	numeric. If type=circle, the radius of the circle (in units of the CRS). If type=rectangle the dimension of the rectangle (one or two numbers).
type	character. The shape of the moving window
win_fun	character. The function to apply to the moving window. The function win_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
agg_fun	character. The function by which to aggregate. By default this is set to mean
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

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 winmove_agg can be run in parallel using plan(multiprocess) from the future package.

Value

Numeric vector containing moving window values calculated for each grid cell

Examples

## Not run: 
# load required data
data(g_sf)
data(cont_ls)
data(cat_ls)

# aggregate using mean
d <- winmove_agg(g_sf, cont_ls, 5, "rectangle", mean)

# aggregate using Shannon evenness
d <- winmove_agg(g_sf, cat_ls, 5, "rectangle", shei, lc_class = 1:4)

## End(Not run)

grainchanger documentation built on Feb. 1, 2021, 5:07 p.m.