R/ee_download.R
In csaybar/rgee: R Bindings for Calling the 'Earth Engine' API
Defines functions
ee_gcs_to_local
ee_drive_to_local
ee_table_to_asset
ee_table_to_gcs
ee_table_to_drive
ee_image_to_asset
ee_image_to_gcs
ee_image_to_drive
Documented in
ee_drive_to_local
ee_gcs_to_local
ee_image_to_asset
ee_image_to_drive
ee_image_to_gcs
ee_table_to_asset
ee_table_to_drive
ee_table_to_gcs
#' Creates a task to export an EE Image to Drive.
#'
#' Creates a task to export an EE Image to Drive.
#' This function is a wrapper around \code{ee$batch$Export$image$toDrive(...)}.
#'
#' @param image The image to be exported.
#' @param description Human-readable name of the task.
#' @param folder The name of a unique folder in your Drive account to be
#' exported into. Defaults to the folder rgee-backup.
#' @param fileNamePrefix The Google Drive filename for the export. Defaults to
#' the name of the task.
#' @param timePrefix Add current date and time as a prefix to files to export.
#' @param 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.
#' @param 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.
#' @param scale The resolution in meters per pixel. Defaults to the native
#' resolution of the image assset unless a crsTransform is specified.
#' @param crs The coordinate reference system of the exported image's
#' projection. Defaults to the image's default projection.
#' @param 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.
#' @param 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.
#' @param shardSize Size in pixels of the shards in which this image
#' will be computed. Defaults to 256.
#' @param 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.
#' @param skipEmptyTiles If TRUE, skip writing empty (i.e. fully-masked)
#' image tiles. Defaults to FALSE.
#' @param fileFormat The string file format to which the image is exported.
#' Currently only 'GeoTIFF' and 'TFRecord' are supported, defaults to 'GeoTIFF'.
#' @param formatOptions A dictionary of string keys to format specific
#' options. **kwargs: Holds other keyword arguments that may have been
#' deprecated such as 'crs_transform', 'driveFolder', and 'driveFileNamePrefix'.
#'
#' @return An unstarted Task that exports the image to Drive.
#' @family image export task creator
#' @examples
#' \dontrun{
#' 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,
#' fileFormat = "GEO_TIFF",
#' region = ee_ROI,
#' fileNamePrefix = "my_image_demo"
#' )
#'
#' task_img$start()
#' ee_monitoring(task_img)
#'
#' # Move results from Drive to local
#' ee_drive_to_local(task = task_img)
#' }
#' @export
ee_image_to_drive <- function(image,
description = "myExportImageTask",
folder = "rgee_backup",
fileNamePrefix = NULL,
timePrefix = TRUE,
dimensions = NULL,
region = NULL,
scale = NULL,
crs = NULL,
crsTransform = NULL,
maxPixels = NULL,
shardSize = NULL,
fileDimensions = NULL,
skipEmptyTiles = NULL,
fileFormat = NULL,
formatOptions = NULL) {
if (isTRUE(timePrefix)) {
timePrefix_chr <- gsub("\\s","_",format(Sys.time(), "%Y_%m_%d_%H_%M_%S"))
if (is.null(fileNamePrefix)) {
fileNamePrefix <- sprintf("%s_%s", description, timePrefix_chr)
} else {
fileNamePrefix <- sprintf("%s_%s", fileNamePrefix, timePrefix_chr)
}
}
ee$batch$Export$image$toDrive(
image = image,
description = description,
folder = folder,
fileNamePrefix = fileNamePrefix,
dimensions = dimensions,
region = region,
scale = scale,
crs = crs,
crsTransform = crsTransform,
maxPixels = maxPixels,
shardSize = shardSize,
fileDimensions = fileDimensions,
skipEmptyTiles = skipEmptyTiles,
fileFormat = fileFormat,
formatOptions = formatOptions
)
}
#' Creates a task to export an EE Image to Google Cloud Storage.
#'
#' Creates a task to export an EE Image to Google Cloud Storage.
#' This function is a wrapper around
#' \code{ee$batch$Export$image$toCloudStorage(...)}.
#'
#' @param image The image to be exported.
#' @param description Human-readable name of the task.
#' @param bucket The name of a Cloud Storage bucket for the export.
#' @param fileNamePrefix Cloud Storage object name prefix for the export.
#' Defaults to the name of the task.
#' @param timePrefix Add current date and time as a prefix to files to export.
#' @param 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.
#' @param 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.
#' @param scale The resolution in meters per pixel. Defaults to the native
#' resolution of the image assset unless a crsTransform is specified.
#' @param crs The coordinate reference system of the exported image's
#' projection. Defaults to the image's default projection.
#' @param 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.
#' @param 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.
#' @param shardSize Size in pixels of the shards in which this image
#' will be computed. Defaults to 256.
#' @param 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.
#' @param skipEmptyTiles If TRUE, skip writing empty (i.e. fully-masked)
#' image tiles. Defaults to FALSE.
#' @param fileFormat The string file format to which the image is exported.
#' Currently only 'GeoTIFF' and 'TFRecord' are supported, defaults
#' to 'GeoTIFF'.
#' @param formatOptions A dictionary of string keys to format specific
#' options. **kwargs: Holds other keyword arguments that may have been
#' deprecated such as 'crs_transform'.
#'
#' @return An unstarted Task that exports the image to Google Cloud Storage.
#' @family image export task creator
#' @examples
#' \dontrun{
#' 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$start()
#' ee_monitoring(task_img)
#'
#' # Move results from GCS to local
#' ee_gcs_to_local(task = task_img)
#'
#' }
#' @export
ee_image_to_gcs <- function(image,
description = "myExportImageTask",
bucket = NULL,
fileNamePrefix = NULL,
timePrefix = TRUE,
dimensions = NULL,
region = NULL,
scale = NULL,
crs = NULL,
crsTransform = NULL,
maxPixels = NULL,
shardSize = NULL,
fileDimensions = NULL,
skipEmptyTiles = NULL,
fileFormat = NULL,
formatOptions = NULL) {
if (is.null(bucket)) {
stop("Cloud Storage bucket was not defined")
}
if (isTRUE(timePrefix)) {
timePrefix_chr <- gsub("\\s","_", format(Sys.time(), "%Y_%m_%d_%H_%M_%S"))
if (is.null(fileNamePrefix)) {
fileNamePrefix <- sprintf("%s_%s", description, timePrefix_chr)
} else {
fileNamePrefix <- sprintf("%s_%s", fileNamePrefix, timePrefix_chr)
}
}
ee$batch$Export$image$toCloudStorage(
image = image,
description = description,
bucket = bucket,
fileNamePrefix = fileNamePrefix,
dimensions = dimensions,
region = region,
scale = scale,
crs = crs,
crsTransform = crsTransform,
maxPixels = maxPixels,
shardSize = shardSize,
fileDimensions = fileDimensions,
skipEmptyTiles = skipEmptyTiles,
fileFormat = fileFormat,
formatOptions = formatOptions
)
}
#' Creates a task to export an EE Image to their EE Assets.
#'
#' Creates a task to export an EE Image to their EE Assets.
#' This function is a wrapper around \code{ee$batch$Export$image$toAsset(...)}.
#'
#'
#' @param image The image to be exported.
#' @param description Human-readable name of the task.
#' @param assetId The destination asset ID.
#' @param overwrite Logical. If TRUE, the assetId will be overwritten if
#' it exists.
#' @param pyramidingPolicy The pyramiding policy to apply to each band
#' in the image, a dictionary keyed by band name. Values must be one
#' of: "mean", "sample", "min", "max", or "mode". Defaults to "mean".
#' A special key, ".default", may be used to change the default for all bands.
#' @param 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.
#' @param 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.
#' @param scale The resolution in meters per pixel. Defaults to the native
#' resolution of the image assset unless a crsTransform is specified.
#' @param crs The coordinate reference system of the exported image's
#' projection. Defaults to the image's default projection.
#' @param 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.
#' @param 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. **kwargs: Holds
#' other keyword arguments that may have been deprecated such
#' as 'crs_transform'.
#'
#' @return An unstarted task
#' @family image export task creator
#' @examples
#' \dontrun{
#' library(rgee)
#' library(stars)
#' library(sf)
#'
#' ee_users()
#' ee_Initialize()
#'
#' # 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
#' assetid <- paste0(ee_get_assethome(), '/l5_Amarakaeri')
#' task_img <- ee_image_to_asset(
#' image = mean_l5_Amarakaeri,
#' assetId = assetid,
#' overwrite = TRUE,
#' scale = 500,
#' region = ee_ROI
#' )
#'
#' task_img$start()
#' ee_monitoring(task_img)
#'
#' ee_l5 <- ee$Image(assetid)
#' Map$centerObject(ee_l5)
#' Map$addLayer(ee_l5)
#' }
#' @export
ee_image_to_asset <- function(image,
description = "myExportImageTask",
assetId = NULL,
overwrite = FALSE,
pyramidingPolicy = NULL,
dimensions = NULL,
region = NULL,
scale = NULL,
crs = NULL,
crsTransform = NULL,
maxPixels = NULL) {
if (isTRUE(overwrite)) {
try(
expr = ee_manage_delete(assetId, quiet = TRUE),
silent = TRUE
)
}
ee$batch$Export$image$toAsset(
image = image,
description = description,
assetId = assetId,
pyramidingPolicy = pyramidingPolicy,
dimensions = dimensions,
region = region,
scale = scale,
crs = crs,
crsTransform = crsTransform,
maxPixels = maxPixels
)
}
#' Creates a task to export a FeatureCollection to Google Drive.
#'
#' Creates a task to export a FeatureCollection to Google Drive.
#' This function is a wrapper around \code{ee$batch$Export$table$toDrive(...)}.
#'
#' @param collection The feature collection to be exported.
#' @param description Human-readable name of the task.
#' @param folder The name of a unique folder in your Drive
#' account to export into. Defaults to the root of the drive.
#' @param fileNamePrefix The Google Drive filename for the
#' export. Defaults to the name of the task.
#' @param timePrefix Add current date and time as a prefix to files to export.
#' @param fileFormat The output format: "CSV" (default), "GeoJSON",
#' "KML", "KMZ", "SHP", or "TFRecord".
#' @param selectors The list of properties to include in the output,
#' as a list of strings or a comma-separated string. By default, all
#' properties are included. **kwargs: Holds other keyword arguments
#' that may have been deprecated such as 'driveFolder' and
#' 'driveFileNamePrefix'.
#'
#' @return An unstarted Task that exports the table to Google Drive.
#' @family vector export task creator
#' @examples
#' \dontrun{
#' 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()
#'
#' amk_fc <- ee$FeatureCollection(
#' list(ee$Feature(ee_ROI, list(name = "Amarakaeri")))
#' )
#'
#' task_vector <- ee_table_to_drive(
#' collection = amk_fc,
#' fileFormat = "GEO_JSON",
#' fileNamePrefix = "geom_Amarakaeri"
#' )
#' task_vector$start()
#' ee_monitoring(task_vector) # optional
#' ee_drive_to_local(task = task_vector)
#' }
#' @export
ee_table_to_drive <- function(collection,
description = "myExportTableTask",
folder = "rgee_backup",
fileNamePrefix = NULL,
timePrefix = TRUE,
fileFormat = NULL,
selectors = NULL) {
if (isTRUE(timePrefix)) {
timePrefix_chr <- gsub("\\s","_", format(Sys.time(), "%Y_%m_%d_%H_%M_%S"))
if (is.null(fileNamePrefix)) {
fileNamePrefix <- sprintf("%s_%s", description, timePrefix_chr)
} else {
fileNamePrefix <- sprintf("%s_%s", fileNamePrefix, timePrefix_chr)
}
}
ee$batch$Export$table$toDrive(
collection = collection,
description = description,
folder = folder,
fileNamePrefix = fileNamePrefix,
fileFormat = fileFormat,
selectors = selectors
)
}
#' Creates a task to export a FeatureCollection to Google Cloud Storage.
#'
#' Creates a task to export a FeatureCollection to Google Cloud Storage.
#' This function is a wrapper around
#' \code{ee$batch$Export$table$toCloudStorage(...)}.
#'
#' @param collection The feature collection to be exported.
#' @param description Human-readable name of the task.
#' @param bucket The name of a Cloud Storage bucket for the export.
#' @param fileNamePrefix Cloud Storage object name prefix
#' for the export. Defaults to the name of the task.
#' @param timePrefix Add current date and time as a prefix to files to export.
#' @param fileFormat The output format: "CSV" (default),
#' "GeoJSON", "KML", "KMZ", "SHP", or "TFRecord".
#' @param selectors The list of properties to include in the output,
#' as a list of strings or a comma-separated string. By default, all
#' properties are included. **kwargs: Holds other keyword arguments
#' that may have been deprecated such as 'outputBucket'.
#'
#' @return An unstarted Task that exports the table to Google Cloud Storage.
#' @family vector export task creator
#' @examples
#' \dontrun{
#' library(rgee)
#' library(stars)
#' library(sf)
#'
#' ee_users()
#' ee_Initialize(gcs = TRUE)
#'
#' # Define study area (local -> earth engine)
#' # Communal Reserve Amarakaeri - Peru
#' rlist <- list(xmin = -71.13, xmax = -70.95,ymin = -12.89, ymax = -12.73)
#' ROI <- c(rlist$xmin, rlist$ymin,
#' rlist$xmax, rlist$ymin,
#' rlist$xmax, rlist$ymax,
#' rlist$xmin, rlist$ymax,
#' rlist$xmin, rlist$ymin)
#' ee_ROI <- matrix(ROI, ncol = 2, byrow = TRUE) %>%
#' list() %>%
#' st_polygon() %>%
#' st_sfc() %>%
#' st_set_crs(4326) %>%
#' sf_as_ee()
#'
#' amk_fc <- ee$FeatureCollection(
#' list(ee$Feature(ee_ROI, list(name = "Amarakaeri")))
#' )
#'
#' task_vector <- ee_table_to_gcs(
#' collection = amk_fc,
#' bucket = "rgee_dev",
#' fileFormat = "SHP",
#' fileNamePrefix = "geom_Amarakaeri"
#' )
#' task_vector$start()
#' ee_monitoring(task_vector) # optional
#' amk_geom <- ee_gcs_to_local(task = task_vector)
#' plot(sf::read_sf(amk_geom[3]), border = "red", lwd = 10)
#' }
#' @export
ee_table_to_gcs <- function(collection,
description = "myExportTableTask",
bucket = NULL,
fileNamePrefix = NULL,
timePrefix = TRUE,
fileFormat = NULL,
selectors = NULL) {
if (is.null(bucket)) {
stop("Cloud Storage bucket was not defined")
}
if (isTRUE(timePrefix)) {
timePrefix_chr <- gsub("\\s","_", format(Sys.time(), "%Y_%m_%d_%H_%M_%S"))
if (is.null(fileNamePrefix)) {
fileNamePrefix <- sprintf("%s_%s", description, timePrefix_chr)
} else {
fileNamePrefix <- sprintf("%s_%s", fileNamePrefix, timePrefix_chr)
}
}
ee$batch$Export$table$toCloudStorage(
collection = collection,
description = description,
bucket = bucket,
fileNamePrefix = fileNamePrefix,
fileFormat = fileFormat,
selectors = selectors
)
}
#' Creates a task to export a FeatureCollection to an EE table asset.
#'
#' Creates a task to export a FeatureCollection to an EE table asset.
#' This function is a wrapper around \code{ee$batch$Export$table$toAsset(...)}.
#'
#' @param collection The feature collection to be exported.
#' @param description Human-readable name of the task.
#' @param assetId The destination asset ID. **kwargs: Holds other
#' keyword arguments that may have been deprecated.
#' @param overwrite Logical. If TRUE, the assetId will be overwritten if
#' it exists.
#'
#' @return An unstarted Task that exports the table to Earth Engine Asset.
#' @family vector export task creator
#' @examples
#' \dontrun{
#' library(rgee)
#' library(stars)
#' library(sf)
#'
#' ee_users()
#' ee_Initialize()
#'
#' # 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()
#'
#' amk_fc <- ee$FeatureCollection(
#' list(ee$Feature(ee_ROI, list(name = "Amarakaeri")))
#' )
#'
#' assetid <- paste0(ee_get_assethome(), '/geom_Amarakaeri')
#' task_vector <- ee_table_to_asset(
#' collection = amk_fc,
#' overwrite = TRUE,
#' assetId = assetid
#' )
#' task_vector$start()
#' ee_monitoring(task_vector) # optional
#'
#' ee_fc <- ee$FeatureCollection(assetid)
#' Map$centerObject(ee_fc)
#' Map$addLayer(ee_fc)
#' }
#' @export
ee_table_to_asset <- function(collection,
description = "myExportTableTask",
assetId = NULL,
overwrite = FALSE) {
if (isTRUE(overwrite)) {
try(
expr = ee_manage_delete(assetId, quiet = TRUE),
silent = TRUE
)
}
ee$batch$Export$table$toAsset(
collection = collection,
description = description,
assetId = assetId
)
}
#' Move results from Google Drive to a local directory
#'
#' Move results of an EE task saved in Google Drive to a local directory.
#'
#' @param task List generated after finished correctly a EE task. See details.
#' @param dsn Character. Output filename. If missing, a temporary
#' file will be assigned.
#' @param overwrite A boolean argument which indicates
#' whether "filename" should be overwritten. By default TRUE.
#' @param consider Interactive. See details.
#' @param public Logical. If TRUE, a public link to the Google Drive resource is
#' created.
#' @param metadata Logical. If TRUE, export the metadata related to the Google
#' Drive resource. See details.
#' @param quiet logical. Suppress info message.
#'
#' @details
#'
#' The task argument needs a status as task "COMPLETED" to work, due that the
#' parameters necessary to identify EE objects into Google Drive are obtained
#' from \code{ee$batch$Export$*$toDrive(...)$start()$status()}.
#'
#' \code{consider} argument is necessary due that Google Drive permits users to
#' create files with the same name. \code{consider} uses an interactive R
#' session by default to help users identify just the files that they want to
#' download. Additionally, the options "last" and "all" are implemented. "last"
#' will download just the last file saved in Google Drive while with "all" all
#' files will be downloaded.
#'
#' Finally if the argument \code{metadata} is TRUE, a list with the
#' following elements are exported join with the output filename (dsn):
#'
#' \itemize{
#' \item{\bold{ee_id: }}{Name of the Earth Engine task.}
#' \item{\bold{drive_name: }}{Name of the Table in Google Drive.}
#' \item{\bold{drive_id: }}{Id of the Table in Google Drive.}
#' \item{\bold{drive_download_link: }}{Download link to the table.}
#' }
#'
#' @importFrom utils menu
#'
#' @return If \code{metadata} is FALSE will return the filename of the Google
#' Drive resource on their system. Otherwise, a list with two elements
#' (\code{dns} and \code{metadata}) is returned.
#'
#' @family generic download functions
#'
#' @examples
#' \dontrun{
#' 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$start()
#' ee_monitoring(task_img)
#'
#' # Move results from Drive to local
#' img <- ee_drive_to_local(task = task_img)
#' }
#' @export
ee_drive_to_local <- function(task,
dsn,
overwrite = TRUE,
consider = TRUE,
public = FALSE,
metadata = FALSE,
quiet = FALSE) {
# Check packages
ee_check_packages("ee_drive_to_local", "googledrive")
# Check credentials
ee_user <- ee_exist_credentials()
if (is.na(ee_user[["drive_cre"]])) {
drive_credential <- ee_create_credentials_drive(ee_user$email)
ee_save_credential(pdrive = drive_credential)
message(
"Google Drive credentials were not loaded.",
" Running ee_Initialize(email = '",ee_user[["email"]],"', drive = TRUE)",
" to fix."
)
}
# global parameter of a task
gd_folder <- basename(ee$batch$Task$status(task)[["destination_uris"]])
gd_ExportOptions <- task[["config"]][["fileExportOptions"]]
gd_filename <- gd_ExportOptions[["driveDestination"]][["filenamePrefix"]]
# Select a google drive file considering the filename and folder
count <- 1
files_gd <- try(googledrive::drive_find(
q = sprintf("'%s' in parents", gd_folder),
q = sprintf("name contains '%s'", gd_filename)
), silent = TRUE)
while (any(class(files_gd) %in% "try-error") & count < 5) {
files_gd <- try(googledrive::drive_find(
q = sprintf("'%s' in parents", gd_folder),
q = sprintf("name contains '%s'", gd_filename)
), silent = TRUE)
count <- count + 1
}
if (public) {
files_gd <- googledrive::drive_share_anyone(files_gd, verbose = FALSE)
}
# (Problem) Google Drive support files with the same name
if (nrow(files_gd) > 0) {
ee_getTime <- function(x) {
gd_file_date <- files_gd[["drive_resource"]][[x]][["createdTime"]]
as.POSIXct(gd_file_date)
}
createdTime <- vapply(seq_len(nrow(files_gd)), ee_getTime, 0)
files_gd <- files_gd[order(createdTime, decreasing = TRUE), ]
if (isTRUE(consider)) {
choices <- c(files_gd[["name"]],'last','all')
if (nrow(files_gd) == 1) {
file_selected <- 1
} else {
file_selected <- menu(
choices = choices,
title = paste0(
"Multiple files with the same name",
" (sorted according to the created time argument):"
)
)
}
if (choices[file_selected] == 'last') {
files_gd <- files_gd[1,]
} else if (choices[file_selected] == 'all') {
files_gd <- files_gd
} else {
files_gd <- files_gd[file_selected, ]
}
} else if (consider == "last") {
files_gd <- files_gd[1, ]
} else if (consider == "all") {
files_gd <- files_gd
} else {
stop("consider argument was not defined properly.")
}
} else {
stop(
"File does not exist in Google Drive.",
" Please verify if the task finished properly."
)
}
# Choose the right file using the driver_resource["originalFilename"]
fileformat <- toupper(gd_ExportOptions[["fileFormat"]])
if (missing(dsn)) {
ee_tempdir <- tempdir()
filenames_local <- sprintf("%s/%s", ee_tempdir, basename(files_gd$name))
} else {
pattern <- "(.*)(\\..*)$"
element_len <- length(files_gd$name)
# Neccesary for large GEOTIFF and TFRecord files
if (task$task_type == "EXPORT_IMAGE" & element_len > 1) {
file_ft <- sprintf(
"-%04d%s",
seq_len(element_len),
sub(pattern, "\\2", files_gd$name)
)
} else {
file_ft <- sub(pattern, "\\2", files_gd$name)
}
dsn_n <- sub(pattern,"\\1",basename(dsn))
filenames_local <- sprintf("%s/%s%s",dirname(dsn), dsn_n, file_ft)
}
# it is necessary for ESRI shapefiles
filenames_local <- ee_sort_localfiles(filenames_local, fileformat)
to_download <- sort_drive_files(files_gd, fileformat)
# if (nrow(to_download) > 4) {
# stop(
# "Impossible to download multiple geometries as SHP.",
# " Try to define the fileFormat argument as GEO_JSON"
# )
# }
for (index in seq_len(nrow(to_download))) {
googledrive::drive_download(
file = to_download[index, ],
path = filenames_local[index],
overwrite = overwrite,
verbose = !quiet
)
}
if (metadata) {
list(
dsn = filenames_local,
metadata = list(
ee_id = task$id,
drive_name = to_download$name,
drive_id = to_download$id,
drive_download_link = sprintf(
"https://drive.google.com/uc?id=%s&export=download",
to_download$id)
)
)
} else {
filenames_local
}
}
#' Move results from Google Cloud Storage to a local directory
#'
#' Move results of an EE task saved in Google Cloud Storage to a local
#' directory.
#'
#' @param task List generated after finished correctly a EE task. See details.
#' @param dsn Character. Output filename. If missing, a temporary
#' file (i.e. \code{tempfile()}) is assigned.
#' @param overwrite A boolean argument which indicates indicating
#' whether "filename" should be overwritten. By default TRUE.
#' @param public Logical. If TRUE, a public link to Google Cloud Storage
#' resource is created.
#' @param metadata Logical. If TRUE, export the metadata related to the Google
#' Cloud Storage resource. See details.
#' @param quiet Logical. Suppress info message
#' @details
#'
#' The task argument needs "COMPLETED" task state to work, since the parameters
#' necessaries to locate the file into google cloud storage are obtained from
#' \code{ee$batch$Export$*$toCloudStorage(...)$start()$status()}.
#'
#' If the argument \code{metadata} is TRUE, a list with the
#' following elements are exported join with the output filename (dsn):
#'
#' \itemize{
#' \item{\bold{ee_id: }}{Name of the Earth Engine task.}
#' \item{\bold{gcs_name: }}{Name of the Table in Google Cloud Storage.}
#' \item{\bold{gcs_bucket: }}{Name of the bucket.}
#' \item{\bold{gcs_fileFormat: }}{Format of the table.}
#' \item{\bold{gcs_public_link: }}{Download link to the table.}
#' \item{\bold{gcs_URI: }}{gs:// link to the table.}
#' }
#'
#' @return If \code{metadata} is FALSE will return the filename of the Google
#' Cloud Storage resource on their system. Otherwise, a list with two elements
#' (\code{dns} and \code{metadata}) is returned.
#'
#' @family generic download functions
#'
#' @examples
#' \dontrun{
#' library(rgee)
#' library(stars)
#' library(sf)
#'
#' ee_users()
#' ee_Initialize(gcs = TRUE)
#'
#' # Define study area (local -> earth engine)
#' # Communal Reserve Amarakaeri - Peru
#' rlist <- list(xmin = -71.13, xmax = -70.95,ymin = -12.89, ymax = -12.73)
#' ROI <- c(rlist$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$start()
#' ee_monitoring(task_img)
#'
#' # Move results from Drive to local
#' img <- ee_gcs_to_local(task = task_img)
#' }
#' @export
ee_gcs_to_local <- function(task,
dsn,
public = FALSE,
metadata = FALSE,
overwrite = TRUE,
quiet = FALSE) {
# Check packages
ee_check_packages("ee_gcs_to_local", "googleCloudStorageR")
# Check credentials
ee_user <- ee_exist_credentials()
if (is.na(ee_user[["gcs_cre"]])) {
gcs_credential <- ee_create_credentials_gcs(ee_user$email)
ee_save_credential(pgcs = gcs_credential[["path"]])
message(
"Google Cloud Storage credentials were not loaded.",
" Running ee_Initialize(email = '",ee_user[["email"]],"', gcs = TRUE)",
" to fix."
)
}
# Getting bucket name and filename
gcs_ExportOptions <- task[["config"]][["fileExportOptions"]]
gcs_bucket <- gcs_ExportOptions[["gcsDestination"]][["bucket"]]
gcs_filename <- gcs_ExportOptions[["gcsDestination"]][["filenamePrefix"]]
gcs_fileFormat <- gcs_ExportOptions[["fileFormat"]]
# Select a gcs file considering the filename and bucket
count <- 1
files_gcs <- try(
expr = googleCloudStorageR::gcs_list_objects(
bucket = gcs_bucket,
prefix = gcs_filename
),
silent = TRUE
)
while (any(class(files_gcs) %in% "try-error") & count < 5) {
files_gcs <- try(
expr = googleCloudStorageR::gcs_list_objects(
bucket = gcs_bucket,
prefix = gcs_filename
),
silent = TRUE
)
count <- count + 1
}
if (public) {
for (name in files_gcs$name) {
googleCloudStorageR::gcs_update_object_acl(
object_name = name,
bucket = gcs_bucket,
entity_type = "allUsers"
)
}
}
# Choose the right file using the driver_resource["originalFilename"]
fileformat <- toupper(gcs_fileFormat)
if (missing(dsn)) {
ee_tempdir <- tempdir()
filenames_local <- sprintf("%s/%s", ee_tempdir, basename(files_gcs[["name"]]))
} else {
pattern <- "(.*)(\\..*)$"
element_len <- length(files_gcs[["name"]])
# Neccesary for large GEOTIFF and TFRecord files
if (task$task_type == "EXPORT_IMAGE" & element_len > 1) {
file_ft <- sprintf(
"-%04d%s",
seq_len(element_len),
sub(pattern, "\\2", files_gcs[["name"]])
)
} else {
file_ft <- sub(pattern, "\\2", files_gcs[["name"]])
}
dsn_n <- sub(pattern,"\\1",basename(dsn))
filenames_local <- sprintf("%s/%s%s",dirname(dsn), dsn_n, file_ft)
}
# it is necessary for ESRI shapefiles
filenames_local <- ee_sort_localfiles(filenames_local, fileformat)
to_download <- sort_drive_files(files_gcs, fileformat)
for (index in seq_along(filenames_local)) {
if (isTRUE(quiet)) {
suppressMessages(
googleCloudStorageR::gcs_get_object(
object_name = to_download[index,][["name"]],
bucket = gcs_bucket,
saveToDisk = filenames_local[index],
overwrite = overwrite
)
)
} else {
googleCloudStorageR::gcs_get_object(
object_name = to_download[index,][["name"]],
bucket = gcs_bucket,
saveToDisk = filenames_local[index],
overwrite = overwrite
)
}
}
if (metadata) {
list(
dsn = filenames_local,
metadata = list(
ee_id = task$id,
gcs_name = to_download$name,
gcs_bucket = gcs_bucket,
gcs_fileFormat = gcs_fileFormat,
gcs_public_link = sprintf(
"https://storage.googleapis.com/%s/%s",
gcs_bucket, to_download$name
),
gcs_URI = sprintf("gs://%s/%s", gcs_bucket, to_download$name)
)
)
} else {
filenames_local
}
}
csaybar/rgee documentation built on March 11, 2021, 5:48 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions ee_gcs_to_local ee_drive_to_local ee_table_to_asset ee_table_to_gcs ee_table_to_drive ee_image_to_asset ee_image_to_gcs ee_image_to_drive
Documented in ee_drive_to_local ee_gcs_to_local ee_image_to_asset ee_image_to_drive ee_image_to_gcs ee_table_to_asset ee_table_to_drive ee_table_to_gcs
#' Creates a task to export an EE Image to Drive.
#'
#' Creates a task to export an EE Image to Drive.
#' This function is a wrapper around \code{ee$batch$Export$image$toDrive(...)}.
#'
#' @param image The image to be exported.
#' @param description Human-readable name of the task.
#' @param folder The name of a unique folder in your Drive account to be
#' exported into. Defaults to the folder rgee-backup.
#' @param fileNamePrefix The Google Drive filename for the export. Defaults to
#' the name of the task.
#' @param timePrefix Add current date and time as a prefix to files to export.
#' @param 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.
#' @param 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.
#' @param scale The resolution in meters per pixel. Defaults to the native
#' resolution of the image assset unless a crsTransform is specified.
#' @param crs The coordinate reference system of the exported image's
#' projection. Defaults to the image's default projection.
#' @param 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.
#' @param 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.
#' @param shardSize Size in pixels of the shards in which this image
#' will be computed. Defaults to 256.
#' @param 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.
#' @param skipEmptyTiles If TRUE, skip writing empty (i.e. fully-masked)
#' image tiles. Defaults to FALSE.
#' @param fileFormat The string file format to which the image is exported.
#' Currently only 'GeoTIFF' and 'TFRecord' are supported, defaults to 'GeoTIFF'.
#' @param formatOptions A dictionary of string keys to format specific
#' options. **kwargs: Holds other keyword arguments that may have been
#' deprecated such as 'crs_transform', 'driveFolder', and 'driveFileNamePrefix'.
#'
#' @return An unstarted Task that exports the image to Drive.
#' @family image export task creator
#' @examples
#' \dontrun{
#' 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,
#' fileFormat = "GEO_TIFF",
#' region = ee_ROI,
#' fileNamePrefix = "my_image_demo"
#' )
#'
#' task_img$start()
#' ee_monitoring(task_img)
#'
#' # Move results from Drive to local
#' ee_drive_to_local(task = task_img)
#' }
#' @export
ee_image_to_drive <- function(image,
description = "myExportImageTask",
folder = "rgee_backup",
fileNamePrefix = NULL,
timePrefix = TRUE,
dimensions = NULL,
region = NULL,
scale = NULL,
crs = NULL,
crsTransform = NULL,
maxPixels = NULL,
shardSize = NULL,
fileDimensions = NULL,
skipEmptyTiles = NULL,
fileFormat = NULL,
formatOptions = NULL) {
if (isTRUE(timePrefix)) {
timePrefix_chr <- gsub("\\s","_",format(Sys.time(), "%Y_%m_%d_%H_%M_%S"))
if (is.null(fileNamePrefix)) {
fileNamePrefix <- sprintf("%s_%s", description, timePrefix_chr)
} else {
fileNamePrefix <- sprintf("%s_%s", fileNamePrefix, timePrefix_chr)
}
}
ee$batch$Export$image$toDrive(
image = image,
description = description,
folder = folder,
fileNamePrefix = fileNamePrefix,
dimensions = dimensions,
region = region,
scale = scale,
crs = crs,
crsTransform = crsTransform,
maxPixels = maxPixels,
shardSize = shardSize,
fileDimensions = fileDimensions,
skipEmptyTiles = skipEmptyTiles,
fileFormat = fileFormat,
formatOptions = formatOptions
)
}
#' Creates a task to export an EE Image to Google Cloud Storage.
#'
#' Creates a task to export an EE Image to Google Cloud Storage.
#' This function is a wrapper around
#' \code{ee$batch$Export$image$toCloudStorage(...)}.
#'
#' @param image The image to be exported.
#' @param description Human-readable name of the task.
#' @param bucket The name of a Cloud Storage bucket for the export.
#' @param fileNamePrefix Cloud Storage object name prefix for the export.
#' Defaults to the name of the task.
#' @param timePrefix Add current date and time as a prefix to files to export.
#' @param 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.
#' @param 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.
#' @param scale The resolution in meters per pixel. Defaults to the native
#' resolution of the image assset unless a crsTransform is specified.
#' @param crs The coordinate reference system of the exported image's
#' projection. Defaults to the image's default projection.
#' @param 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.
#' @param 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.
#' @param shardSize Size in pixels of the shards in which this image
#' will be computed. Defaults to 256.
#' @param 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.
#' @param skipEmptyTiles If TRUE, skip writing empty (i.e. fully-masked)
#' image tiles. Defaults to FALSE.
#' @param fileFormat The string file format to which the image is exported.
#' Currently only 'GeoTIFF' and 'TFRecord' are supported, defaults
#' to 'GeoTIFF'.
#' @param formatOptions A dictionary of string keys to format specific
#' options. **kwargs: Holds other keyword arguments that may have been
#' deprecated such as 'crs_transform'.
#'
#' @return An unstarted Task that exports the image to Google Cloud Storage.
#' @family image export task creator
#' @examples
#' \dontrun{
#' 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$start()
#' ee_monitoring(task_img)
#'
#' # Move results from GCS to local
#' ee_gcs_to_local(task = task_img)
#'
#' }
#' @export
ee_image_to_gcs <- function(image,
description = "myExportImageTask",
bucket = NULL,
fileNamePrefix = NULL,
timePrefix = TRUE,
dimensions = NULL,
region = NULL,
scale = NULL,
crs = NULL,
crsTransform = NULL,
maxPixels = NULL,
shardSize = NULL,
fileDimensions = NULL,
skipEmptyTiles = NULL,
fileFormat = NULL,
formatOptions = NULL) {
if (is.null(bucket)) {
stop("Cloud Storage bucket was not defined")
}
if (isTRUE(timePrefix)) {
timePrefix_chr <- gsub("\\s","_", format(Sys.time(), "%Y_%m_%d_%H_%M_%S"))
if (is.null(fileNamePrefix)) {
fileNamePrefix <- sprintf("%s_%s", description, timePrefix_chr)
} else {
fileNamePrefix <- sprintf("%s_%s", fileNamePrefix, timePrefix_chr)
}
}
ee$batch$Export$image$toCloudStorage(
image = image,
description = description,
bucket = bucket,
fileNamePrefix = fileNamePrefix,
dimensions = dimensions,
region = region,
scale = scale,
crs = crs,
crsTransform = crsTransform,
maxPixels = maxPixels,
shardSize = shardSize,
fileDimensions = fileDimensions,
skipEmptyTiles = skipEmptyTiles,
fileFormat = fileFormat,
formatOptions = formatOptions
)
}
#' Creates a task to export an EE Image to their EE Assets.
#'
#' Creates a task to export an EE Image to their EE Assets.
#' This function is a wrapper around \code{ee$batch$Export$image$toAsset(...)}.
#'
#'
#' @param image The image to be exported.
#' @param description Human-readable name of the task.
#' @param assetId The destination asset ID.
#' @param overwrite Logical. If TRUE, the assetId will be overwritten if
#' it exists.
#' @param pyramidingPolicy The pyramiding policy to apply to each band
#' in the image, a dictionary keyed by band name. Values must be one
#' of: "mean", "sample", "min", "max", or "mode". Defaults to "mean".
#' A special key, ".default", may be used to change the default for all bands.
#' @param 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.
#' @param 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.
#' @param scale The resolution in meters per pixel. Defaults to the native
#' resolution of the image assset unless a crsTransform is specified.
#' @param crs The coordinate reference system of the exported image's
#' projection. Defaults to the image's default projection.
#' @param 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.
#' @param 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. **kwargs: Holds
#' other keyword arguments that may have been deprecated such
#' as 'crs_transform'.
#'
#' @return An unstarted task
#' @family image export task creator
#' @examples
#' \dontrun{
#' library(rgee)
#' library(stars)
#' library(sf)
#'
#' ee_users()
#' ee_Initialize()
#'
#' # 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
#' assetid <- paste0(ee_get_assethome(), '/l5_Amarakaeri')
#' task_img <- ee_image_to_asset(
#' image = mean_l5_Amarakaeri,
#' assetId = assetid,
#' overwrite = TRUE,
#' scale = 500,
#' region = ee_ROI
#' )
#'
#' task_img$start()
#' ee_monitoring(task_img)
#'
#' ee_l5 <- ee$Image(assetid)
#' Map$centerObject(ee_l5)
#' Map$addLayer(ee_l5)
#' }
#' @export
ee_image_to_asset <- function(image,
description = "myExportImageTask",
assetId = NULL,
overwrite = FALSE,
pyramidingPolicy = NULL,
dimensions = NULL,
region = NULL,
scale = NULL,
crs = NULL,
crsTransform = NULL,
maxPixels = NULL) {
if (isTRUE(overwrite)) {
try(
expr = ee_manage_delete(assetId, quiet = TRUE),
silent = TRUE
)
}
ee$batch$Export$image$toAsset(
image = image,
description = description,
assetId = assetId,
pyramidingPolicy = pyramidingPolicy,
dimensions = dimensions,
region = region,
scale = scale,
crs = crs,
crsTransform = crsTransform,
maxPixels = maxPixels
)
}
#' Creates a task to export a FeatureCollection to Google Drive.
#'
#' Creates a task to export a FeatureCollection to Google Drive.
#' This function is a wrapper around \code{ee$batch$Export$table$toDrive(...)}.
#'
#' @param collection The feature collection to be exported.
#' @param description Human-readable name of the task.
#' @param folder The name of a unique folder in your Drive
#' account to export into. Defaults to the root of the drive.
#' @param fileNamePrefix The Google Drive filename for the
#' export. Defaults to the name of the task.
#' @param timePrefix Add current date and time as a prefix to files to export.
#' @param fileFormat The output format: "CSV" (default), "GeoJSON",
#' "KML", "KMZ", "SHP", or "TFRecord".
#' @param selectors The list of properties to include in the output,
#' as a list of strings or a comma-separated string. By default, all
#' properties are included. **kwargs: Holds other keyword arguments
#' that may have been deprecated such as 'driveFolder' and
#' 'driveFileNamePrefix'.
#'
#' @return An unstarted Task that exports the table to Google Drive.
#' @family vector export task creator
#' @examples
#' \dontrun{
#' 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()
#'
#' amk_fc <- ee$FeatureCollection(
#' list(ee$Feature(ee_ROI, list(name = "Amarakaeri")))
#' )
#'
#' task_vector <- ee_table_to_drive(
#' collection = amk_fc,
#' fileFormat = "GEO_JSON",
#' fileNamePrefix = "geom_Amarakaeri"
#' )
#' task_vector$start()
#' ee_monitoring(task_vector) # optional
#' ee_drive_to_local(task = task_vector)
#' }
#' @export
ee_table_to_drive <- function(collection,
description = "myExportTableTask",
folder = "rgee_backup",
fileNamePrefix = NULL,
timePrefix = TRUE,
fileFormat = NULL,
selectors = NULL) {
if (isTRUE(timePrefix)) {
timePrefix_chr <- gsub("\\s","_", format(Sys.time(), "%Y_%m_%d_%H_%M_%S"))
if (is.null(fileNamePrefix)) {
fileNamePrefix <- sprintf("%s_%s", description, timePrefix_chr)
} else {
fileNamePrefix <- sprintf("%s_%s", fileNamePrefix, timePrefix_chr)
}
}
ee$batch$Export$table$toDrive(
collection = collection,
description = description,
folder = folder,
fileNamePrefix = fileNamePrefix,
fileFormat = fileFormat,
selectors = selectors
)
}
#' Creates a task to export a FeatureCollection to Google Cloud Storage.
#'
#' Creates a task to export a FeatureCollection to Google Cloud Storage.
#' This function is a wrapper around
#' \code{ee$batch$Export$table$toCloudStorage(...)}.
#'
#' @param collection The feature collection to be exported.
#' @param description Human-readable name of the task.
#' @param bucket The name of a Cloud Storage bucket for the export.
#' @param fileNamePrefix Cloud Storage object name prefix
#' for the export. Defaults to the name of the task.
#' @param timePrefix Add current date and time as a prefix to files to export.
#' @param fileFormat The output format: "CSV" (default),
#' "GeoJSON", "KML", "KMZ", "SHP", or "TFRecord".
#' @param selectors The list of properties to include in the output,
#' as a list of strings or a comma-separated string. By default, all
#' properties are included. **kwargs: Holds other keyword arguments
#' that may have been deprecated such as 'outputBucket'.
#'
#' @return An unstarted Task that exports the table to Google Cloud Storage.
#' @family vector export task creator
#' @examples
#' \dontrun{
#' library(rgee)
#' library(stars)
#' library(sf)
#'
#' ee_users()
#' ee_Initialize(gcs = TRUE)
#'
#' # Define study area (local -> earth engine)
#' # Communal Reserve Amarakaeri - Peru
#' rlist <- list(xmin = -71.13, xmax = -70.95,ymin = -12.89, ymax = -12.73)
#' ROI <- c(rlist$xmin, rlist$ymin,
#' rlist$xmax, rlist$ymin,
#' rlist$xmax, rlist$ymax,
#' rlist$xmin, rlist$ymax,
#' rlist$xmin, rlist$ymin)
#' ee_ROI <- matrix(ROI, ncol = 2, byrow = TRUE) %>%
#' list() %>%
#' st_polygon() %>%
#' st_sfc() %>%
#' st_set_crs(4326) %>%
#' sf_as_ee()
#'
#' amk_fc <- ee$FeatureCollection(
#' list(ee$Feature(ee_ROI, list(name = "Amarakaeri")))
#' )
#'
#' task_vector <- ee_table_to_gcs(
#' collection = amk_fc,
#' bucket = "rgee_dev",
#' fileFormat = "SHP",
#' fileNamePrefix = "geom_Amarakaeri"
#' )
#' task_vector$start()
#' ee_monitoring(task_vector) # optional
#' amk_geom <- ee_gcs_to_local(task = task_vector)
#' plot(sf::read_sf(amk_geom[3]), border = "red", lwd = 10)
#' }
#' @export
ee_table_to_gcs <- function(collection,
description = "myExportTableTask",
bucket = NULL,
fileNamePrefix = NULL,
timePrefix = TRUE,
fileFormat = NULL,
selectors = NULL) {
if (is.null(bucket)) {
stop("Cloud Storage bucket was not defined")
}
if (isTRUE(timePrefix)) {
timePrefix_chr <- gsub("\\s","_", format(Sys.time(), "%Y_%m_%d_%H_%M_%S"))
if (is.null(fileNamePrefix)) {
fileNamePrefix <- sprintf("%s_%s", description, timePrefix_chr)
} else {
fileNamePrefix <- sprintf("%s_%s", fileNamePrefix, timePrefix_chr)
}
}
ee$batch$Export$table$toCloudStorage(
collection = collection,
description = description,
bucket = bucket,
fileNamePrefix = fileNamePrefix,
fileFormat = fileFormat,
selectors = selectors
)
}
#' Creates a task to export a FeatureCollection to an EE table asset.
#'
#' Creates a task to export a FeatureCollection to an EE table asset.
#' This function is a wrapper around \code{ee$batch$Export$table$toAsset(...)}.
#'
#' @param collection The feature collection to be exported.
#' @param description Human-readable name of the task.
#' @param assetId The destination asset ID. **kwargs: Holds other
#' keyword arguments that may have been deprecated.
#' @param overwrite Logical. If TRUE, the assetId will be overwritten if
#' it exists.
#'
#' @return An unstarted Task that exports the table to Earth Engine Asset.
#' @family vector export task creator
#' @examples
#' \dontrun{
#' library(rgee)
#' library(stars)
#' library(sf)
#'
#' ee_users()
#' ee_Initialize()
#'
#' # 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()
#'
#' amk_fc <- ee$FeatureCollection(
#' list(ee$Feature(ee_ROI, list(name = "Amarakaeri")))
#' )
#'
#' assetid <- paste0(ee_get_assethome(), '/geom_Amarakaeri')
#' task_vector <- ee_table_to_asset(
#' collection = amk_fc,
#' overwrite = TRUE,
#' assetId = assetid
#' )
#' task_vector$start()
#' ee_monitoring(task_vector) # optional
#'
#' ee_fc <- ee$FeatureCollection(assetid)
#' Map$centerObject(ee_fc)
#' Map$addLayer(ee_fc)
#' }
#' @export
ee_table_to_asset <- function(collection,
description = "myExportTableTask",
assetId = NULL,
overwrite = FALSE) {
if (isTRUE(overwrite)) {
try(
expr = ee_manage_delete(assetId, quiet = TRUE),
silent = TRUE
)
}
ee$batch$Export$table$toAsset(
collection = collection,
description = description,
assetId = assetId
)
}
#' Move results from Google Drive to a local directory
#'
#' Move results of an EE task saved in Google Drive to a local directory.
#'
#' @param task List generated after finished correctly a EE task. See details.
#' @param dsn Character. Output filename. If missing, a temporary
#' file will be assigned.
#' @param overwrite A boolean argument which indicates
#' whether "filename" should be overwritten. By default TRUE.
#' @param consider Interactive. See details.
#' @param public Logical. If TRUE, a public link to the Google Drive resource is
#' created.
#' @param metadata Logical. If TRUE, export the metadata related to the Google
#' Drive resource. See details.
#' @param quiet logical. Suppress info message.
#'
#' @details
#'
#' The task argument needs a status as task "COMPLETED" to work, due that the
#' parameters necessary to identify EE objects into Google Drive are obtained
#' from \code{ee$batch$Export$*$toDrive(...)$start()$status()}.
#'
#' \code{consider} argument is necessary due that Google Drive permits users to
#' create files with the same name. \code{consider} uses an interactive R
#' session by default to help users identify just the files that they want to
#' download. Additionally, the options "last" and "all" are implemented. "last"
#' will download just the last file saved in Google Drive while with "all" all
#' files will be downloaded.
#'
#' Finally if the argument \code{metadata} is TRUE, a list with the
#' following elements are exported join with the output filename (dsn):
#'
#' \itemize{
#' \item{\bold{ee_id: }}{Name of the Earth Engine task.}
#' \item{\bold{drive_name: }}{Name of the Table in Google Drive.}
#' \item{\bold{drive_id: }}{Id of the Table in Google Drive.}
#' \item{\bold{drive_download_link: }}{Download link to the table.}
#' }
#'
#' @importFrom utils menu
#'
#' @return If \code{metadata} is FALSE will return the filename of the Google
#' Drive resource on their system. Otherwise, a list with two elements
#' (\code{dns} and \code{metadata}) is returned.
#'
#' @family generic download functions
#'
#' @examples
#' \dontrun{
#' 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$start()
#' ee_monitoring(task_img)
#'
#' # Move results from Drive to local
#' img <- ee_drive_to_local(task = task_img)
#' }
#' @export
ee_drive_to_local <- function(task,
dsn,
overwrite = TRUE,
consider = TRUE,
public = FALSE,
metadata = FALSE,
quiet = FALSE) {
# Check packages
ee_check_packages("ee_drive_to_local", "googledrive")
# Check credentials
ee_user <- ee_exist_credentials()
if (is.na(ee_user[["drive_cre"]])) {
drive_credential <- ee_create_credentials_drive(ee_user$email)
ee_save_credential(pdrive = drive_credential)
message(
"Google Drive credentials were not loaded.",
" Running ee_Initialize(email = '",ee_user[["email"]],"', drive = TRUE)",
" to fix."
)
}
# global parameter of a task
gd_folder <- basename(ee$batch$Task$status(task)[["destination_uris"]])
gd_ExportOptions <- task[["config"]][["fileExportOptions"]]
gd_filename <- gd_ExportOptions[["driveDestination"]][["filenamePrefix"]]
# Select a google drive file considering the filename and folder
count <- 1
files_gd <- try(googledrive::drive_find(
q = sprintf("'%s' in parents", gd_folder),
q = sprintf("name contains '%s'", gd_filename)
), silent = TRUE)
while (any(class(files_gd) %in% "try-error") & count < 5) {
files_gd <- try(googledrive::drive_find(
q = sprintf("'%s' in parents", gd_folder),
q = sprintf("name contains '%s'", gd_filename)
), silent = TRUE)
count <- count + 1
}
if (public) {
files_gd <- googledrive::drive_share_anyone(files_gd, verbose = FALSE)
}
# (Problem) Google Drive support files with the same name
if (nrow(files_gd) > 0) {
ee_getTime <- function(x) {
gd_file_date <- files_gd[["drive_resource"]][[x]][["createdTime"]]
as.POSIXct(gd_file_date)
}
createdTime <- vapply(seq_len(nrow(files_gd)), ee_getTime, 0)
files_gd <- files_gd[order(createdTime, decreasing = TRUE), ]
if (isTRUE(consider)) {
choices <- c(files_gd[["name"]],'last','all')
if (nrow(files_gd) == 1) {
file_selected <- 1
} else {
file_selected <- menu(
choices = choices,
title = paste0(
"Multiple files with the same name",
" (sorted according to the created time argument):"
)
)
}
if (choices[file_selected] == 'last') {
files_gd <- files_gd[1,]
} else if (choices[file_selected] == 'all') {
files_gd <- files_gd
} else {
files_gd <- files_gd[file_selected, ]
}
} else if (consider == "last") {
files_gd <- files_gd[1, ]
} else if (consider == "all") {
files_gd <- files_gd
} else {
stop("consider argument was not defined properly.")
}
} else {
stop(
"File does not exist in Google Drive.",
" Please verify if the task finished properly."
)
}
# Choose the right file using the driver_resource["originalFilename"]
fileformat <- toupper(gd_ExportOptions[["fileFormat"]])
if (missing(dsn)) {
ee_tempdir <- tempdir()
filenames_local <- sprintf("%s/%s", ee_tempdir, basename(files_gd$name))
} else {
pattern <- "(.*)(\\..*)$"
element_len <- length(files_gd$name)
# Neccesary for large GEOTIFF and TFRecord files
if (task$task_type == "EXPORT_IMAGE" & element_len > 1) {
file_ft <- sprintf(
"-%04d%s",
seq_len(element_len),
sub(pattern, "\\2", files_gd$name)
)
} else {
file_ft <- sub(pattern, "\\2", files_gd$name)
}
dsn_n <- sub(pattern,"\\1",basename(dsn))
filenames_local <- sprintf("%s/%s%s",dirname(dsn), dsn_n, file_ft)
}
# it is necessary for ESRI shapefiles
filenames_local <- ee_sort_localfiles(filenames_local, fileformat)
to_download <- sort_drive_files(files_gd, fileformat)
# if (nrow(to_download) > 4) {
# stop(
# "Impossible to download multiple geometries as SHP.",
# " Try to define the fileFormat argument as GEO_JSON"
# )
# }
for (index in seq_len(nrow(to_download))) {
googledrive::drive_download(
file = to_download[index, ],
path = filenames_local[index],
overwrite = overwrite,
verbose = !quiet
)
}
if (metadata) {
list(
dsn = filenames_local,
metadata = list(
ee_id = task$id,
drive_name = to_download$name,
drive_id = to_download$id,
drive_download_link = sprintf(
"https://drive.google.com/uc?id=%s&export=download",
to_download$id)
)
)
} else {
filenames_local
}
}
#' Move results from Google Cloud Storage to a local directory
#'
#' Move results of an EE task saved in Google Cloud Storage to a local
#' directory.
#'
#' @param task List generated after finished correctly a EE task. See details.
#' @param dsn Character. Output filename. If missing, a temporary
#' file (i.e. \code{tempfile()}) is assigned.
#' @param overwrite A boolean argument which indicates indicating
#' whether "filename" should be overwritten. By default TRUE.
#' @param public Logical. If TRUE, a public link to Google Cloud Storage
#' resource is created.
#' @param metadata Logical. If TRUE, export the metadata related to the Google
#' Cloud Storage resource. See details.
#' @param quiet Logical. Suppress info message
#' @details
#'
#' The task argument needs "COMPLETED" task state to work, since the parameters
#' necessaries to locate the file into google cloud storage are obtained from
#' \code{ee$batch$Export$*$toCloudStorage(...)$start()$status()}.
#'
#' If the argument \code{metadata} is TRUE, a list with the
#' following elements are exported join with the output filename (dsn):
#'
#' \itemize{
#' \item{\bold{ee_id: }}{Name of the Earth Engine task.}
#' \item{\bold{gcs_name: }}{Name of the Table in Google Cloud Storage.}
#' \item{\bold{gcs_bucket: }}{Name of the bucket.}
#' \item{\bold{gcs_fileFormat: }}{Format of the table.}
#' \item{\bold{gcs_public_link: }}{Download link to the table.}
#' \item{\bold{gcs_URI: }}{gs:// link to the table.}
#' }
#'
#' @return If \code{metadata} is FALSE will return the filename of the Google
#' Cloud Storage resource on their system. Otherwise, a list with two elements
#' (\code{dns} and \code{metadata}) is returned.
#'
#' @family generic download functions
#'
#' @examples
#' \dontrun{
#' library(rgee)
#' library(stars)
#' library(sf)
#'
#' ee_users()
#' ee_Initialize(gcs = TRUE)
#'
#' # Define study area (local -> earth engine)
#' # Communal Reserve Amarakaeri - Peru
#' rlist <- list(xmin = -71.13, xmax = -70.95,ymin = -12.89, ymax = -12.73)
#' ROI <- c(rlist$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$start()
#' ee_monitoring(task_img)
#'
#' # Move results from Drive to local
#' img <- ee_gcs_to_local(task = task_img)
#' }
#' @export
ee_gcs_to_local <- function(task,
dsn,
public = FALSE,
metadata = FALSE,
overwrite = TRUE,
quiet = FALSE) {
# Check packages
ee_check_packages("ee_gcs_to_local", "googleCloudStorageR")
# Check credentials
ee_user <- ee_exist_credentials()
if (is.na(ee_user[["gcs_cre"]])) {
gcs_credential <- ee_create_credentials_gcs(ee_user$email)
ee_save_credential(pgcs = gcs_credential[["path"]])
message(
"Google Cloud Storage credentials were not loaded.",
" Running ee_Initialize(email = '",ee_user[["email"]],"', gcs = TRUE)",
" to fix."
)
}
# Getting bucket name and filename
gcs_ExportOptions <- task[["config"]][["fileExportOptions"]]
gcs_bucket <- gcs_ExportOptions[["gcsDestination"]][["bucket"]]
gcs_filename <- gcs_ExportOptions[["gcsDestination"]][["filenamePrefix"]]
gcs_fileFormat <- gcs_ExportOptions[["fileFormat"]]
# Select a gcs file considering the filename and bucket
count <- 1
files_gcs <- try(
expr = googleCloudStorageR::gcs_list_objects(
bucket = gcs_bucket,
prefix = gcs_filename
),
silent = TRUE
)
while (any(class(files_gcs) %in% "try-error") & count < 5) {
files_gcs <- try(
expr = googleCloudStorageR::gcs_list_objects(
bucket = gcs_bucket,
prefix = gcs_filename
),
silent = TRUE
)
count <- count + 1
}
if (public) {
for (name in files_gcs$name) {
googleCloudStorageR::gcs_update_object_acl(
object_name = name,
bucket = gcs_bucket,
entity_type = "allUsers"
)
}
}
# Choose the right file using the driver_resource["originalFilename"]
fileformat <- toupper(gcs_fileFormat)
if (missing(dsn)) {
ee_tempdir <- tempdir()
filenames_local <- sprintf("%s/%s", ee_tempdir, basename(files_gcs[["name"]]))
} else {
pattern <- "(.*)(\\..*)$"
element_len <- length(files_gcs[["name"]])
# Neccesary for large GEOTIFF and TFRecord files
if (task$task_type == "EXPORT_IMAGE" & element_len > 1) {
file_ft <- sprintf(
"-%04d%s",
seq_len(element_len),
sub(pattern, "\\2", files_gcs[["name"]])
)
} else {
file_ft <- sub(pattern, "\\2", files_gcs[["name"]])
}
dsn_n <- sub(pattern,"\\1",basename(dsn))
filenames_local <- sprintf("%s/%s%s",dirname(dsn), dsn_n, file_ft)
}
# it is necessary for ESRI shapefiles
filenames_local <- ee_sort_localfiles(filenames_local, fileformat)
to_download <- sort_drive_files(files_gcs, fileformat)
for (index in seq_along(filenames_local)) {
if (isTRUE(quiet)) {
suppressMessages(
googleCloudStorageR::gcs_get_object(
object_name = to_download[index,][["name"]],
bucket = gcs_bucket,
saveToDisk = filenames_local[index],
overwrite = overwrite
)
)
} else {
googleCloudStorageR::gcs_get_object(
object_name = to_download[index,][["name"]],
bucket = gcs_bucket,
saveToDisk = filenames_local[index],
overwrite = overwrite
)
}
}
if (metadata) {
list(
dsn = filenames_local,
metadata = list(
ee_id = task$id,
gcs_name = to_download$name,
gcs_bucket = gcs_bucket,
gcs_fileFormat = gcs_fileFormat,
gcs_public_link = sprintf(
"https://storage.googleapis.com/%s/%s",
gcs_bucket, to_download$name
),
gcs_URI = sprintf("gs://%s/%s", gcs_bucket, to_download$name)
)
)
} else {
filenames_local
}
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.