Convert an Earth Engine table in a sf object

ee_as_sf(
  x,
  dsn,
  overwrite = TRUE,
  crs = NULL,
  via = "getInfo",
  maxFeatures = 5000,
  container = "rgee_backup",
  selectors = NULL,
  quiet = FALSE
)

Arguments

x	Earth Engine table (ee$FeatureCollection) to be converted into a sf object.
dsn	Character. Output filename; in case `dsn` is missing `ee_as_sf` will create a temporary file.
overwrite	Logical. Delete data source `dsn` before attempting to write?.
crs	Integer or character. coordinate reference system for the EE table. If is NULL, `ee_as_sf` will take the CRS of the first element.
via	Character. Method to fetch data about the object. Multiple options supported. See details.
maxFeatures	Numeric. The maximum allowed number of features to export (ignore if `via` is not set as "getInfo"). The task will fail if the exported region covers more features. Defaults to 5000.
container	Character. Name of the folder ('drive') or bucket ('gcs') to be exported into (ignore if `via` is not defined as "drive" or "gcs").
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.
quiet	logical. Suppress info message

Value

An sf object.

Details

ee_as_sf supports the download of ee$FeatureCollection, ee$Feature and ee$Geometry by three different options: "getInfo", "drive", and "gcs". When "getInfo" is set in the via argument, ee_as_sf will make an REST call to retrieve all the known information about the object. The advantage of use "getInfo" is a direct and faster download. However, there is a limitation of 5000 features by request which makes it not recommendable for large collections. Instead of "getInfo", the options: "drive" and "gcs" are suitable for large collections since they use an intermediate container, which may be Google Drive and Google Cloud Storage respectively. For getting more information about exporting data from Earth Engine, take a look at the Google Earth Engine Guide - Export data.

Examples

if (FALSE) {
library(rgee)

ee_Initialize(drive = TRUE, gcs = TRUE)

# Region of interest
roi <- ee$Geometry$Polygon(list(
  c(-122.275, 37.891),
  c(-122.275, 37.868),
  c(-122.240, 37.868),
  c(-122.240, 37.891)
))

# TIGER: US Census Blocks Dataset
blocks <- ee$FeatureCollection("TIGER/2010/Blocks")
subset <- blocks$filterBounds(roi)
sf_subset <- ee_as_sf(x = subset)
plot(sf_subset)

# Create Random points in Earth Engine
region <- ee$Geometry$Rectangle(-119.224, 34.669, -99.536, 50.064)
ee_help(ee$FeatureCollection$randomPoints)
ee_randomPoints <- ee$FeatureCollection$randomPoints(region, 100)

# Download via GetInfo
sf_randomPoints <- ee_as_sf(ee_randomPoints)
plot(sf_randomPoints)

# Download via drive
sf_randomPoints_drive <- ee_as_sf(
  x = ee_randomPoints,
  via = 'drive'
)

# Download via GCS
# sf_randomPoints_gcs <- ee_as_sf(
#   x = subset,
#   via = 'gcs',
#   container = 'rgee_dev' #GCS bucket name
# )
}