rgee (version 0.5.0)

ee_gcs_to_local: 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, overwrite = TRUE, quiet = FALSE)

Arguments

task

List generated after finished correctly a EE task. See details.

dsn

Character. Output filename. If missing, a temporary file will be assigned.

overwrite

Logical. A boolean indicating whether the file should be overwritten.

quiet

Logical. Suppress info message

Value

filename character vector.

Details

The task argument needs "COMPLETED" task state to work, since the parameters necessaries to locate the file into google cloud storage are obtained from ee$batch$Export$*$toCloudStorage(...)$start()$status().

Examples

# NOT RUN {
library(rgee)
library(stars)
library(sf)

ee_users()
ee_reattach() # reattach ee as a reserved word
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_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$geometry(),
    fileNamePrefix = paste0("my_image", Sys.time())
)

task_img$start()
ee_monitoring(task_img)

# Move results from Drive to local
img <- ee_gcs_to_local(task = task_img)
# }