Select a data cube band by name

Description

Select a data cube band by name

Extract a subset of a data cube

Usage

## S3 method for class 'cube'
x$name

## S3 method for class 'cube'
cube[ib = TRUE, it = TRUE, iy = TRUE, ix = TRUE, ...]

Arguments

Details

The [] operator allows for flexible subsetting of data cubes by date, datetime, bounding box, spatial points, and band names. Depending on the arguments, it supports slicing ( selecting one element of a dimension) and cropping (selecting a subinterval of a dimension) and combinations thereof (e.g., selecting a spatial window and a temporal slice). Dimension subsets can be specified by integer indexes or coordinates / datetime values. Arguments are matched by type and order. For example, if the first argument is a length-two vector of type Date, the function will realize that this is for subsetting the time dimension. If needed, arguments are treated in the order band, time, y, x.

Note

This function returns a proxy object, i.e., it will not start any computations besides deriving the shape of the result.

This function returns a proxy object, i.e., it will not start any computations besides deriving the shape of the result.

Examples

# 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="P3M", aggregation = "median")
L8.cube = raster_cube(L8.col, v, mask=image_mask("BQA", bits=4, values=16))
L8.red = L8.cube$B04


plot(L8.red)

# 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="2018-01-01", t1="2018-12-31"),
              srs="EPSG:32618", nx = 497, ny=526, dt="P1D", aggregation = "median")
L8.cube = raster_cube(L8.col, v, mask=image_mask("BQA", bits=4, values=16))

L8.cube[c("B05","B04")] # select bands
L8.cube[as.Date(c("2018-01-10", "2018-01-20"))] # crop by time
L8.cube[as.Date("2018-01-10")] # slice by time
L8.cube["B05", "2018-01-10"] # select bands and slice by time
L8.cube["B05", c("2018-01-10","2018-01-17")] # select bands and crop by time
L8.cube[, c("2018-01-10","2018-01-17")] # crop by time

# crop by space (coordinates and integer indexes respectively)
L8.cube[list(left=388941.2 + 1e5, right=766552.4 - 1e5, bottom=4345299 + 1e5, top=4744931 - 1e5)]
L8.cube[,,c(1,100), c(1,100)] 

L8.cube[,c(1,2),,] # crop by time (integer indexes)

# select by spatial point or bounding box
if (requireNamespace("sf", quietly = TRUE)) {
  s = sf::st_sfc(sf::st_point(c(500000, 4500000)), crs = "EPSG:32618")
  L8.cube[s]

  bbox =  sf::st_bbox(c(xmin = 388941.2 + 1e5, xmax = 766552.4 - 1e5,
                   ymax = 4744931 - 1e5, ymin = 4345299 + 1e5), crs = sf::st_crs(32618))
  L8.cube[bbox]
}