gdalcubes (version 0.2.5)

reduce_space.cube: Reduce a data cube over spatial (x,y or lat,lon) dimensions

Description

Create a proxy data cube, which applies one or more reducer functions to selected bands over spatial slices of a data cube

Usage

# S3 method for cube
reduce_space(x, expr, ...)

Arguments

x

source data cube

expr

either a single string, or a vector of strings defining which reducers will be applied over which bands of the input cube

...

optional additional expressions (if expr is not a vector)

Value

proxy data cube object

Details

Notice that expressions have a very simple format: the reducer is followed by the name of a band in parantheses. You cannot add more complex functions or arguments.

Possible reducers currently are "min", "max", "sum", "prod", "count", "mean", "median", "var", "sd".

Examples

# NOT RUN {
# create image collection from example Landsat data only 
# if not already done in other examples
if (!file.exists(file.path(tempdir(), "L8.db"))) {
  L8_files <- list.files(system.file("L8NY18", package = "gdalcubes"),
                         ".TIF", recursive = TRUE, full.names = TRUE)
  create_image_collection(L8_files, "L8_L1TP", file.path(tempdir(), "L8.db")) 
}

L8.col = image_collection(file.path(tempdir(), "L8.db"))
v = cube_view(extent=list(left=388941.2, right=766552.4, 
              bottom=4345299, top=4744931, t0="2018-01", t1="2018-12"),
              srs="EPSG:32618", nx = 497, ny=526, dt="P1M")
L8.cube = raster_cube(L8.col, v) 
L8.b02 = select_bands(L8.cube, c("B02"))
L8.b02.median = reduce_space(L8.b02, "median(B02)")  
L8.b02.median
# }