# Creates a task to export an EE Image to Google Cloud Storage. Creates a task to export an EE Image to Google Cloud Storage. This function is a wrapper around `ee$batch$Export$image$toCloudStorage(...)`. ```r 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 ) ``` ## Arguments - `image`: The image to be exported. - `description`: User-friendly name of the task. - `bucket`: Cloud Storage bucket name for the export. - `fileNamePrefix`: Cloud Storage object name prefix for the export. Defaults to the name of the task. - `timePrefix`: Prefixes the current date and time to the exported files - `dimensions`: Defines the image dimensions for export. It can be specified as a single positive integer for the maximum dimension or in "WIDTHxHEIGHT" format, where WIDTH and HEIGHT are positive integers. - `region`: The lon,lat coordinates for a LinearRing or Polygon specifying the region to export. It can be specified as nested lists of numbers or a serialized string. Defaults to the image's region. - `scale`: Image resolution in meters per pixel. Defaults to the native resolution of the image asset 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`: Maximum number of pixels allowed in the exported image. The task will fail if the exported region exceeds this limit in the specified projection. Defaults to 100,000,000. - `shardSize`: Size given in pixels of the shards in which the image will be computed. Defaults to 256. - `fileDimensions`: Defines the pixel dimensions for each image file when the image size exceeds the capacity of a single file.To indicate a square shape, use a single number; for width and height, use a list of two dimensions. Please note that the image will be clipped to the overall image dimensions. The specified file dimensions must be a multiple of the 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'. ## Returns An unstarted Task that exports the image to Google Cloud Storage. ## Examples ```r ## 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) ``` ## See Also Other image export task creator: `ee_image_to_asset()`, `ee_image_to_drive()`

ee_image_to_gcs function