ee_gcs_to_local {rgee}

Move results from Google Cloud Storage to a local directory

Description

Move results of an EE task saved in Google Cloud Storage to a local directory.

Usage

ee_gcs_to_local(
  task,
  dsn,
  public = FALSE,
  metadata = FALSE,
  overwrite = TRUE,
  quiet = FALSE
)

Arguments

task

List generated after the EE task is correctly finished. See details.

dsn

Character. Output filename. If missing, a temporary file (i.e. tempfile()) will be assigned.

public

Logical. If TRUE, a public link to Google Cloud Storage resource is created. "Public Access Prevention" may need to be removed. In addition, the bucket access control configuration must be "fine-grained". See GCS public files documentation for more details.

metadata

Logical. If TRUE, export the metadata related to the Google Cloud Storage resource. See details.

overwrite

A boolean argument that indicates whether "filename" should be overwritten. By default TRUE.

quiet

Logical. Suppress info message

Details

The task argument requires a status of "COMPLETED" because the parameters required to identify EE items in Google Drive are retrieved from ee$batch$Export$*$toCloudStorage(...)$start()$status().

If the argument metadata is TRUE, a list containing the following elements is exported and appended to the output filename (dsn):

• ee_id: Name of the Earth Engine task.

• gcs_name: Name of the Table in Google Cloud Storage.

• gcs_bucket: Name of the bucket.

• gcs_fileFormat: Format of the table.

• gcs_public_link: Download link to the table.

• gcs_URI: gs:// link to the table.

Value

If metadata is FALSE, will return the filename of the Google Cloud Storage resource on their system. Otherwise, a list with two elements (dns and metadata) is returned.

See Also

Other generic download functions: ee_drive_to_local()

Examples

## 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 Drive
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 Drive to local
img <- ee_gcs_to_local(task = task_img)

## End(Not run)