R: Create a data cube from an image collection

raster_cube {gdalcubes} | R Documentation

## Create a data cube from an image collection

### Description

Create a proxy data cube, which loads data from a given image collection according to a data cube view

### Usage

    raster_cube(
      image_collection,
      view,
      mask = NULL,
      chunking = .pkgenv$default_chunksize
    )

### Arguments

`image_collection` | Source image collection as from `image_collection` or `create_image_collection`
`view` | A data cube view defining the shape (spatiotemporal extent, resolution, and spatial reference), if missing, a default overview is used
`mask` | mask pixels of images based on band values, see `image_mask`
`chunking` | length-3 vector or a function returning a vector of length 3, defining the size of data cube chunks in the order time, y, x.

### Details

The following steps will be performed when the data cube is requested to read data of a chunk:

1. Find images from the input collection that intersect with the spatiotemporal extent of the chunk 2. For all resulting images, apply gdalwarp to reproject, resize, and resample to an in-memory GDAL dataset 3. Read the resulting data to the chunk buffer and optionally apply a mask on the result 4. Update pixel-wise aggregator (as defined in the data cube view) to combine values of multiple images within the same data cube pixels

If chunking is provided as a function, it must accept exactly three arguments for the total size of the cube in t, y, and x axes (in this order).

### Value

A proxy data cube object

### 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"))
    }

    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")
    raster_cube(L8.col, v)

     # using a mask on the Landsat quality bit band to filter out clouds
     raster_cube(L8.col, v, mask=image_mask("BQA", bits=4, values=16))

[Package gdalcubes version 0.6.0 Index]