Methods to coerce odcr classes to native spatial classes

as.stars() allows to convert xarray.core.dataset.Dataset to stars.

as.raster() allows to convert xarray.core.dataset.Dataset to RasterLayer or RasterBrick.

as.stars(from)

as.raster(from)

Arguments

from	object of class xarray.core.dataset.Dataset

Value

as.stars() retruns an object of class stars

as.raster() retruns an object of class RasterLayer or RasterBrick or a list of such in case of more than 3 dimensions

Examples

if (FALSE) {
library(odcr)

# connect to a database, store the Daatcube connection internally (default and recommended)
database_connect(app = "Sentinel_2")

# build a query list
lat <- 22.821
lon <- 28.518
buffer <- 0.05

query <- list(
  'time' = c('2020-01', '2020-03'),
  'x' = c(lon - buffer, lon + buffer),
  'y' = c(lat + buffer, lat - buffer),
  'output_crs' = 'epsg:6933',
  'resolution' = c(-20,20)
)

# load data and return an xarray object for a query
ds <- dc_load(query = c(product = "s2_l2a", dask_chunks = dict(), query))
ds <- ds[,101:300,101:300]

# convert to stars (multi-dimensional and mulit-varariable)
ds_stars <- as.stars(ds)
ds_stars <- as(ds, "stars")

# convert to stars (single variable)
ds_stars <- as.stars(ds[[1]])

# convert to stars (2-dim, multi-variable)
ds_stars <- as.stars(ds[1,,])

# convert to raster (multi-dimensional and mulit-varariable)
ds_raster <- as.raster(ds)
ds_raster <- as(ds, "raster")
# raster cannot represent 4-dim objects, thus coereced to list of RasterBricks

# convert to starasterrs (single variable)
ds_raster <- as.raster(ds[[1]])

# convert to raster (2-dim, multi-variable)
ds_raster <- as.raster(ds[1,,])
}