ee_table_to_gcs: Creates a task to export a FeatureCollection to Google Cloud...

In csaybar/rgee: R Bindings for Calling the 'Earth Engine' API

Description

Creates a task to export a FeatureCollection to Google Cloud Storage. This function is a wrapper around ee$batch$Export$table$toCloudStorage(...).

Usage

ee_table_to_gcs(
  collection,
  description = "myExportTableTask",
  bucket = NULL,
  fileNamePrefix = NULL,
  timePrefix = TRUE,
  fileFormat = NULL,
  selectors = NULL
)

Arguments

collection	The feature collection 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.
fileFormat	The output format: "CSV" (default), "GeoJSON", "KML", "KMZ", "SHP", or "TFRecord".
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'.

Value

An unstarted Task that exports the table to Google Cloud Storage.

See Also

Other vector export task creator: ee_table_to_asset(), ee_table_to_drive()

Examples

## 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()

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)

## End(Not run)

csaybar/rgee documentation built on March 11, 2021, 5:48 a.m.