gdalcubes (version 0.2.5)

raster_cube: 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 = c(16, 256, 256))

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

Vector of length 3 defining the size of data cube chunks in the order time, y, x.

Value

A proxy data cube object

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

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")
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))
 
# }