ee_drive_to_local: Move results from Google Drive to a local directory

Description

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

Usage

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

Value

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

Arguments

task: A generated list obtained after completing an Earth Engine task. See details.
dsn: Character. Output filename. If missing, a temporary file will be assigned.
overwrite: A boolean argument that indicates whether filename should be overwritten. By default TRUE.
consider: Interactive. See details.
public: Logical. If TRUE, a public link to the Google Drive resource is created.
metadata: Logical. If TRUE, the metadata related to the Google Drive resource will be exported. See details.
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$*$toDrive(...)$start()$status().

Due to the fact that Google Drive allows users to create files with the same name, the consider argument is required. It use an interactive R session by default to assist users in identifying the specific files they wish to download. Additionally, "last" and "all" settings are provided. "last" will only download the most recently saved file in Google Drive, whereas "all" will download all files with the same name.

Finally, 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.
drive_name: Name of the Table in Google Drive.
drive_id: Id of the Table in Google Drive.
drive_download_link: Download link to the table.

Examples

Run this code

if (FALSE) {
library(rgee)
library(stars)
library(sf)

ee_users()
ee_Initialize(drive = 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_drive(
  image = mean_l5_Amarakaeri,
  folder = "Amarakaeri",
  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_drive_to_local(task = task_img)
}