sits (version 1.5.3)

sits_cube.stac_cube: Create data cubes from image collections accessible by STAC

Description

Creates a data cube based on spatial and temporal restrictions in collections accessible by the STAC protocol

Usage

# S3 method for stac_cube
sits_cube(
  source,
  collection,
  ...,
  bands = NULL,
  tiles = NULL,
  roi = NULL,
  crs = NULL,
  start_date = NULL,
  end_date = NULL,
  orbit = "descending",
  platform = NULL,
  multicores = 2L,
  progress = TRUE
)

Value

A tibble describing the contents of a data cube.

Arguments

source

Data source: one of "AWS", "BDC", "CDSE", "DEAFRICA", "DEAUSTRALIA", "HLS", "PLANETSCOPE", "MPC", "SDC" or "USGS".

collection

Image collection in data source. To find out the supported collections, use sits_list_collections()).

...

Other parameters to be passed for specific types.

bands

Spectral bands and indices to be included in the cube (optional). Use sits_list_collections() to find out the bands available for each collection.

tiles

Tiles from the collection to be included in the cube (see details below).

roi

Region of interest (see below).

crs

The Coordinate Reference System (CRS) of the roi. (see details below).

start_date, end_date

Initial and final dates to include images from the collection in the cube (optional). (Date in YYYY-MM-DD format).

orbit

Orbit name ("ascending", "descending") for SAR cubes.

platform

Optional parameter specifying the platform in case of "LANDSAT" collection. Options: Landsat-5, Landsat-7, Landsat-8, Landsat-9.

multicores

Number of workers for parallel processing (integer, min = 1, max = 2048).

progress

Logical: show a progress bar?

Examples

if (sits_run_examples()) {
    # --- Creating Sentinel cube from MPC
    s2_cube <- sits_cube(
        source = "MPC",
        collection = "SENTINEL-2-L2A",
        tiles = "20LKP",
        bands = c("B05", "CLOUD"),
        start_date = "2018-07-18",
        end_date = "2018-08-23"
    )

    # --- Creating Landsat cube from MPC
    roi <- c(
        "lon_min" = -50.410, "lon_max" = -50.379,
        "lat_min" = -10.1910, "lat_max" = -10.1573
    )
    mpc_cube <- sits_cube(
        source = "MPC",
        collection = "LANDSAT-C2-L2",
        bands = c("BLUE", "RED", "CLOUD"),
        roi = roi,
        start_date = "2005-01-01",
        end_date = "2006-10-28"
    )

    ## Sentinel-1 SAR from MPC
    roi_sar <- c(
        "lon_min" = -50.410, "lon_max" = -50.379,
        "lat_min" = -10.1910, "lat_max" = -10.1573
    )

    s1_cube_open <- sits_cube(
        source = "MPC",
        collection = "SENTINEL-1-GRD",
        bands = c("VV", "VH"),
        orbit = "descending",
        roi = roi_sar,
        start_date = "2020-06-01",
        end_date = "2020-09-28"
    )
    # --- Access to the Brazil Data Cube
    # create a raster cube file based on the information in the BDC
    cbers_tile <- sits_cube(
        source = "BDC",
        collection = "CBERS-WFI-16D",
        bands = c("NDVI", "EVI"),
        tiles = "007004",
        start_date = "2018-09-01",
        end_date = "2019-08-28"
    )
    # --- Access to Digital Earth Africa
    # create a raster cube file based on the information about the files
    # DEAFRICA does not support definition of tiles
    cube_deafrica <- sits_cube(
        source = "DEAFRICA",
        collection = "SENTINEL-2-L2A",
        bands = c("B04", "B08"),
        roi = c(
            "lat_min" = 17.379,
            "lon_min" = 1.1573,
            "lat_max" = 17.410,
            "lon_max" = 1.1910
        ),
        start_date = "2019-01-01",
        end_date = "2019-10-28"
    )
    # --- Access to Digital Earth Australia
    cube_deaustralia <- sits_cube(
        source = "DEAUSTRALIA",
        collection = "GA_LS8CLS9C_GM_CYEAR_3",
        bands = c("RED", "GREEN", "BLUE"),
        roi = c(
            lon_min = 137.15991,
            lon_max = 138.18467,
            lat_min = -33.85777,
            lat_max = -32.56690
        ),
        start_date = "2018-01-01",
        end_date = "2018-12-31"
    )
    # --- Access to CDSE open data Sentinel 2/2A level 2 collection
    # --- remember to set the appropriate environmental variables
    # It is recommended that `multicores` be used to accelerate the process.
    s2_cube <- sits_cube(
        source = "CDSE",
        collection = "SENTINEL-2-L2A",
        tiles = c("20LKP"),
        bands = c("B04", "B08", "B11"),
        start_date = "2018-07-18",
        end_date = "2019-01-23"
    )

    ## --- Sentinel-1 SAR from CDSE
    # --- remember to set the appropriate environmental variables
    # --- Obtain a AWS_ACCESS_KEY_ID and AWS_ACCESS_SECRET_KEY_ID
    # --- from CDSE
    roi_sar <- c(
        "lon_min" = 33.546, "lon_max" = 34.999,
        "lat_min" = 1.427, "lat_max" = 3.726
    )
    s1_cube_open <- sits_cube(
        source = "CDSE",
        collection = "SENTINEL-1-RTC",
        bands = c("VV", "VH"),
        orbit = "descending",
        roi = roi_sar,
        start_date = "2020-01-01",
        end_date = "2020-06-10"
    )


    # -- Access to World Cover data (2021) via Terrascope
    cube_terrascope <- sits_cube(
        source = "TERRASCOPE",
        collection = "WORLD-COVER-2021",
        roi = c(
            lon_min = -62.7,
            lon_max = -62.5,
            lat_min = -8.83,
            lat_max = -8.70
        )
    )
}