ee_image_to_gcs: Creates a task to export an EE Image to Google Cloud Storage.
In csaybar/rgee: R Bindings for Calling the 'Earth Engine' API

Description Usage Arguments Value See Also Examples

Creates a task to export an EE Image to Google Cloud Storage. This function is a wrapper around ee$batch$Export$image$toCloudStorage(...).

ee_image_to_gcs(
  image,
  description = "myExportImageTask",
  bucket = NULL,
  fileNamePrefix = NULL,
  timePrefix = TRUE,
  dimensions = NULL,
  region = NULL,
  scale = NULL,
  crs = NULL,
  crsTransform = NULL,
  maxPixels = NULL,
  shardSize = NULL,
  fileDimensions = NULL,
  skipEmptyTiles = NULL,
  fileFormat = NULL,
  formatOptions = NULL
)

`image`	The image to be exported.
`description`	Human-readable name of the task.
`bucket`	The name of a Cloud Storage bucket for the export.
`fileNamePrefix`	Cloud Storage object name prefix for the export. Defaults to the name of the task.
`timePrefix`	Add current date and time as a prefix to files to export.
`dimensions`	The dimensions of the exported image. Takes either a single positive integer as the maximum dimension or "WIDTHxHEIGHT" where WIDTH and HEIGHT are each positive integers.
`region`	The lon,lat coordinates for a LinearRing or Polygon specifying the region to export. Can be specified as a nested lists of numbers or a serialized string. Defaults to the image's region.
`scale`	The resolution in meters per pixel. Defaults to the native resolution of the image assset unless a crsTransform is specified.
`crs`	The coordinate reference system of the exported image's projection. Defaults to the image's default projection.
`crsTransform`	A comma-separated string of 6 numbers describing the affine transform of the coordinate reference system of the exported image's projection, in the order: xScale, xShearing, xTranslation, yShearing, yScale and yTranslation. Defaults to the image's native CRS transform.
`maxPixels`	The maximum allowed number of pixels in the exported image. The task will fail if the exported region covers more pixels in the specified projection. Defaults to 100,000,000.
`shardSize`	Size in pixels of the shards in which this image will be computed. Defaults to 256.
`fileDimensions`	The dimensions in pixels of each image file, if the image is too large to fit in a single file. May specify a single number to indicate a square shape, or a list of two dimensions to indicate (width,height). Note that the image will still be clipped to the overall image dimensions. Must be a multiple of shardSize.
`skipEmptyTiles`	If TRUE, skip writing empty (i.e. fully-masked) image tiles. Defaults to FALSE.
`fileFormat`	The string file format to which the image is exported. Currently only 'GeoTIFF' and 'TFRecord' are supported, defaults to 'GeoTIFF'.
`formatOptions`	A dictionary of string keys to format specific options. **kwargs: Holds other keyword arguments that may have been deprecated such as 'crs_transform'.

An unstarted Task that exports the image to Google Cloud Storage.

Other image export task creator: ee_image_to_asset(), ee_image_to_drive()

## Not run: 
library(rgee)
library(stars)
library(sf)

ee_users()
ee_Initialize(gcs = TRUE)

# Define study area (local -> earth engine)
# Communal Reserve Amarakaeri - Peru
rlist <- list(xmin = -71.13, xmax = -70.95,ymin = -12.89, ymax = -12.73)
ROI <- c(rlist$xmin, rlist$ymin,
         rlist$xmax, rlist$ymin,
         rlist$xmax, rlist$ymax,
         rlist$xmin, rlist$ymax,
         rlist$xmin, rlist$ymin)
ee_ROI <- matrix(ROI, ncol = 2, byrow = TRUE) %>%
  list() %>%
  st_polygon() %>%
  st_sfc() %>%
  st_set_crs(4326) %>%
  sf_as_ee()


# Get the mean annual NDVI for 2011
cloudMaskL457 <- function(image) {
  qa <- image$select("pixel_qa")
  cloud <- qa$bitwiseAnd(32L)$
    And(qa$bitwiseAnd(128L))$
    Or(qa$bitwiseAnd(8L))
  mask2 <- image$mask()$reduce(ee$Reducer$min())
  image <- image$updateMask(cloud$Not())$updateMask(mask2)
  image$normalizedDifference(list("B4", "B3"))
}

ic_l5 <- ee$ImageCollection("LANDSAT/LT05/C01/T1_SR")$
  filterBounds(ee$FeatureCollection(ee_ROI))$
  filterDate("2011-01-01", "2011-12-31")$
  map(cloudMaskL457)

# Create simple composite
mean_l5 <- ic_l5$mean()$rename("NDVI")
mean_l5 <- mean_l5$reproject(crs = "EPSG:4326", scale = 500)
mean_l5_Amarakaeri <- mean_l5$clip(ee_ROI)

# Move results from Earth Engine to GCS
task_img <- ee_image_to_gcs(
 image = mean_l5_Amarakaeri,
 bucket = "rgee_dev",
 fileFormat = "GEO_TIFF",
 region = ee_ROI,
 fileNamePrefix = "my_image_demo"
)

task_img$start()
ee_monitoring(task_img)

# Move results from GCS to local
ee_gcs_to_local(task = task_img)


## End(Not run)