gdalcubes_selection

Subsetting data cubes

Description

Subset data cube dimensions and bands / variables.

Usage

$.cube(x, name)

[.cube(x, ib = TRUE, it = TRUE, iy = TRUE, ix = TRUE, ...)

Arguments

Argument Description
x source data cube
name character; name of selected band
ib first selector (optional), object of type character, list, Date, POSIXt, numeric, [sf::st_bbox](sf::st_bbox), or [sf::st_sfc](sf::st_sfc), see Details and examples
it second selector (optional), see ib
iy third selector (optional), see ib
ix fourth selector (optional), see ib
… further arguments, not used

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), 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 understand to subset the time dimension. Otherwise, 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.

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"), quiet = TRUE) 
}
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)


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
A data cube proxy object

Dimensions:
         low       high count       pixel_size chunk_size
t 2018-01-01 2018-12-31   365              P1D          1
y    4345299    4744931   526 759.756653992395        384
x   388941.2   766552.4   497 759.781086519115        384

Bands:
  name offset scale nodata unit
1  B05      0     1    NaN     
2  B04      0     1    NaN     
L8.cube[as.Date(c("2018-01-10", "2018-01-20"))] # crop by time
A data cube proxy object

Dimensions:
         low       high count       pixel_size chunk_size
t 2018-01-10 2018-01-20    11              P1D          1
y    4345299    4744931   526 759.756653992395        384
x   388941.2   766552.4   497 759.781086519115        384

Bands:
   name offset scale nodata unit
1   B01      0     1    NaN     
2   B02      0     1    NaN     
3   B03      0     1    NaN     
4   B04      0     1    NaN     
5   B05      0     1    NaN     
6   B06      0     1    NaN     
7   B07      0     1    NaN     
8   B08      0     1    NaN     
9   B09      0     1    NaN     
10  B10      0     1    NaN     
11  B11      0     1    NaN     
12  BQA      0     1    NaN     
L8.cube[as.Date("2018-01-10")] # slice by time
A data cube proxy object

Dimensions:
         low       high count       pixel_size chunk_size
t 2018-01-10 2018-01-10     1              P1D          1
y    4345299    4744931   526 759.756653992395        384
x   388941.2   766552.4   497 759.781086519115        384

Bands:
   name offset scale nodata unit
1   B01      0     1    NaN     
2   B02      0     1    NaN     
3   B03      0     1    NaN     
4   B04      0     1    NaN     
5   B05      0     1    NaN     
6   B06      0     1    NaN     
7   B07      0     1    NaN     
8   B08      0     1    NaN     
9   B09      0     1    NaN     
10  B10      0     1    NaN     
11  B11      0     1    NaN     
12  BQA      0     1    NaN     
L8.cube["B05", "2018-01-10"] # select bands and slice by time
A data cube proxy object

Dimensions:
         low       high count       pixel_size chunk_size
t 2018-01-10 2018-01-10     1              P1D          1
y    4345299    4744931   526 759.756653992395        384
x   388941.2   766552.4   497 759.781086519115        384

Bands:
  name offset scale nodata unit
1  B05      0     1    NaN     
L8.cube["B05", c("2018-01-10","2018-01-17")] # select bands and crop by time
A data cube proxy object

Dimensions:
         low       high count       pixel_size chunk_size
t 2018-01-10 2018-01-17     8              P1D          1
y    4345299    4744931   526 759.756653992395        384
x   388941.2   766552.4   497 759.781086519115        384

Bands:
  name offset scale nodata unit
1  B05      0     1    NaN     
L8.cube[, c("2018-01-10","2018-01-17")] # crop by time
A data cube proxy object

Dimensions:
         low       high count       pixel_size chunk_size
t 2018-01-10 2018-01-17     8              P1D          1
y    4345299    4744931   526 759.756653992395        384
x   388941.2   766552.4   497 759.781086519115        384

Bands:
   name offset scale nodata unit
1   B01      0     1    NaN     
2   B02      0     1    NaN     
3   B03      0     1    NaN     
4   B04      0     1    NaN     
5   B05      0     1    NaN     
6   B06      0     1    NaN     
7   B07      0     1    NaN     
8   B08      0     1    NaN     
9   B09      0     1    NaN     
10  B10      0     1    NaN     
11  B11      0     1    NaN     
12  BQA      0     1    NaN     
# 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)]
A data cube proxy object

Dimensions:
               low             high count       pixel_size chunk_size
t       2018-01-01       2018-12-31   365              P1D          1
y   4445586.878327   4644643.121673   262 759.756653992395        384
x 489232.303420523 666261.296579477   233 759.781086519115        384

Bands:
   name offset scale nodata unit
1   B01      0     1    NaN     
2   B02      0     1    NaN     
3   B03      0     1    NaN     
4   B04      0     1    NaN     
5   B05      0     1    NaN     
6   B06      0     1    NaN     
7   B07      0     1    NaN     
8   B08      0     1    NaN     
9   B09      0     1    NaN     
10  B10      0     1    NaN     
11  B11      0     1    NaN     
12  BQA      0     1    NaN     
L8.cube[,,c(1,100), c(1,100)] 
A data cube proxy object

Dimensions:
               low             high count       pixel_size chunk_size
t       2018-01-01       2018-12-31   365              P1D          1
y 4668195.57794677 4744171.24334601   100 759.756653992394        384
x 389700.981086519 465679.089738431   100 759.781086519114        384

Bands:
   name offset scale nodata unit
1   B01      0     1    NaN     
2   B02      0     1    NaN     
3   B03      0     1    NaN     
4   B04      0     1    NaN     
5   B05      0     1    NaN     
6   B06      0     1    NaN     
7   B07      0     1    NaN     
8   B08      0     1    NaN     
9   B09      0     1    NaN     
10  B10      0     1    NaN     
11  B11      0     1    NaN     
12  BQA      0     1    NaN     
L8.cube[,c(1,2),,] # crop by time (integer indexes)
A data cube proxy object

Dimensions:
         low       high count       pixel_size chunk_size
t 2018-01-02 2018-01-03     2              P1D          1
y    4345299    4744931   526 759.756653992395        384
x   388941.2   766552.4   497 759.781086519115        384

Bands:
   name offset scale nodata unit
1   B01      0     1    NaN     
2   B02      0     1    NaN     
3   B03      0     1    NaN     
4   B04      0     1    NaN     
5   B05      0     1    NaN     
6   B06      0     1    NaN     
7   B07      0     1    NaN     
8   B08      0     1    NaN     
9   B09      0     1    NaN     
10  B10      0     1    NaN     
11  B11      0     1    NaN     
12  BQA      0     1    NaN     
# subset 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]
}

A data cube proxy object

Dimensions:
               low             high count       pixel_size chunk_size
t       2018-01-01       2018-12-31   365              P1D          1
y   4445586.878327   4644643.121673   262 759.756653992395        384
x 489232.303420523 666261.296579477   233 759.781086519115        384

Bands:
   name offset scale nodata unit
1   B01      0     1    NaN     
2   B02      0     1    NaN     
3   B03      0     1    NaN     
4   B04      0     1    NaN     
5   B05      0     1    NaN     
6   B06      0     1    NaN     
7   B07      0     1    NaN     
8   B08      0     1    NaN     
9   B09      0     1    NaN     
10  B10      0     1    NaN     
11  B11      0     1    NaN     
12  BQA      0     1    NaN