Convert an Earth Engine table in an sf object
Convert an Earth Engine table in an sf object
ee_as_sf( x, dsn, overwrite = TRUE, via = "getInfo", container = "rgee_backup", crs = NULL, maxFeatures = 5000, selectors = NULL, lazy = FALSE, public = TRUE, add_metadata = TRUE, timePrefix = TRUE, quiet = FALSE )
x |
Earth Engine table (ee$FeatureCollection) to be converted in an sf object. |
dsn |
Character. Output filename. In case |
overwrite |
Logical. Delete data source |
via |
Character. Method to export the image. Three method are implemented: "getInfo", "drive", "gcs". See details. |
container |
Character. Name of the folder ('drive') or bucket ('gcs')
to be exported into (ignore if |
crs |
Integer or Character. Coordinate Reference System (CRS)
for the EE table. If it is NULL, |
maxFeatures |
Numeric. The maximum allowed number of features to
export (ignore if |
selectors |
The list of properties to include in the output, as a list/vector of strings or a comma-separated string. By default, all properties are included. |
lazy |
Logical. If TRUE, a |
public |
Logical. If TRUE, a public link to the file is created. See details. |
add_metadata |
Add metadata to the sf object. See details. |
timePrefix |
Logical. Add current date and time ( |
quiet |
logical. Suppress info message. |
ee_as_sf supports the download of ee$Geometry, ee$Feature,
and ee$FeatureCollection by three different options:
"getInfo" (which make an REST call to retrieve the data), "drive"
(which use Google Drive)
and "gcs" (which use
Google Cloud Storage). The advantage of use "getInfo" is a
direct and faster download. However, there is a limitation of 5000 features by
request, making it not recommendable for large FeatureCollection. Instead of
"getInfo", the options: "drive" and "gcs" are suitable for large FeatureCollections
due to the use of an intermediate container. When via is set as "drive" or "gcs"
ee_as_sf perform the following steps:
1. A task is started (i.e., ee$batch$Task$start()) to
move the EE Table from Earth Engine to the file storage system (Google Drive
or Google Cloud Storage) specified in the argument via.
2. If the argument lazy is TRUE, the task will not be
monitored. This is useful to lunch several tasks simultaneously and
calls them later using ee_utils_future_value or
future::value. At the end of this step,
the EE Table is stored on the path specified in the argument
dsn.
3. Finally, if the argument add_metadata is TRUE, a list
with the following elements is added to the sf object.
if via is "drive":
ee_id: Name of the Earth Engine task.
drive_name: Name of the Table in Google Drive.
drive_id: Id of the Table in Google Drive.
drive_download_link: Download link to the table.
if via is "gcs":
ee_id: Name of the Earth Engine task.
gcs_name: Name of the Table in Google Cloud Storage.
gcs_bucket: Name of the bucket.
gcs_fileFormat: Format of the table.
gcs_public_link: Download link to the table.
gcs_URI: gs:// link to the table.
Run attr(sf, "metadata") to get the list.
For getting more information about exporting data from Earth Engine, take a look at the Google Earth Engine Guide - Export data.
An sf object.
## Not run:
library(rgee)
ee_Initialize(drive = TRUE, gcs = TRUE)
# Region of interest
roi <- ee$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
)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.