R/ee_download.R
ee_image_to_gcs.Rd
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()
if (FALSE) { 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" # ) # # task_img$start() # ee_monitoring(task_img) # Move results from GCS to local # ee_gcs_to_local(task = task_img) # plot(img) }