rgee has two types of dependencies: strict dependencies that must be satisfied before the rgee installation and the credentials dependencies that unlock rgee import & export functions.

If the first group of dependencies is not fulfilled rgee just will not work. The dependencies that comprised this group are:

  • Google account with Earth Engine activated
  • Python >= v3.5
  • EarthEngine Python API (Python package)

The activation of Earth Engine accounts depends on each user, check the oficial website of Google Earth Engine for more details. If you do not count with a Python environment or a version of the EarthEngine Python API, we strongly recommend you run ee_install(py_env = "rgee"). This function will realize the following six tasks:

  1. If you do not count with a Python environment, it will display an interactive menu to install Miniconda (a free minimal installer for conda).
  2. Remove the previous Python environment defined in py_env if it exist.
  3. Create a new Python environment.
  4. Set the environmental variable EARTHENGINE_PYTHON. It is used to define RETICULATE_PYTHON when the library is loaded. See this article for further details.
  5. Install rgee Python dependencies. Using reticulate::py_install.
  6. Interactive menu to confirm if restart the R session to see changes.

However, the use of ee_install() is not mandatory. You can count on with your own custom installation. This would be also allowed.

ee_install() # It is just neccessary once!

By the other hand, the credentials dependencies are only needed to move data from Google Drive and Google Cloud Storage to your local environment. These dependencies are not mandatory. However, they will help you to create a seamless connection between R and Earth Engine. The dependencies that comprised this group are shown below:

  • Google Cloud Storage credential
  • Google Drive credential

Import and Export Spatial Data using rgee

The batch import/export involves difficulties for most GEE users. In rgee, we are aware of it and we created several functions to help users to download and upload spatial data. If you are trying to export data from Earth Engine, rgee offers the following options:

Table 1. Download functions provided by the rgee package.
Image ee_image_to_drive EE server Drive Unstarted task
ee_image_to_gcs EE server Cloud Storage Unstarted task
ee_image_to_asset EE server EE asset Unstarted task
ee_as_raster EE server Local RasterStack object
ee_as_stars EE server Local Proxy-stars object
Table ee_table_to_drive EE server Drive Unstarted task
ee_table_to_gcs EE server Cloud Storage Unstarted task
ee_table_to_asset EE server EE asset Unstarted task
ee_as_sf EE server Local sf object
Generic ee_drive_to_local Drive Local object filename
ee_gcs_to_local Cloud Storage Local GCS filename

In rgee, all the functions from server to local side have the option to fetch data using an intermediate container (Google Drive or Google Cloud Storage) or through a REST call (“$getInfo”). Although the latter option performs a quick download, there is a request limit of 262144 pixels for ee$Image and 5000 elements for ee$FeatureCollection which makes it unsuitable for large objects. Other download functions, from server-side to others (see Table 1), are implemented to enable more customized download workflows. For example, using ee_image_to_drive and ee_drive_to_local users could create scripts which save results in the .TFRecord rather than the .GeoTIFF format. rgee to deal with Google Drive and Google Cloud Storage use the R package googledrive and googleCloudStorageR respectively, so you will need to install it before.

# please try as follow

Google Drive is more friendly to novice Earth Engine users because the authentication process could be done without leaving R. However, if you are trying to move large images or vectors, is preferable use Google Cloud Storage instead. For using Google Cloud Storage, you will need to have your own Google Project with a credit card added to the service, charges will apply. See the GCS_AUTH_FILE tutorial to create your own service account key. If you want to understand why this is necessary, please have a look at Mark Edmondson tutorial.

Batch upload is a harder process, in rgee we try to make it simple. If you want to upload files in a batch way, firstly you must get authorization to read & write into a Google Cloud Storage (GCS) bucket. rgee implement the next functions:

Table 2. Upload functions provided by the rgee package.
Image gcs_to_ee_image Cloud Storage EE asset EE Asset ID
raster_as_ee Local EE asset EE Asset ID
stars_as_ee Local EE asset EE Asset ID
Table gcs_to_ee_table Cloud Storage EE asset EE Asset ID
sf_as_ee Local EE asset EE Asset ID
Generic local_to_gcs Local Cloud Storage GCS filename

The upload process follows the same logic (Table 2). rgee includes raster_as_ee and stars_as_ee for uploading images and sf_as_ee for uploading vector data.


As we have seen previously, rgee deal with three different Google API’s:

  • Google Earth Engine
  • Google Drive
  • Google Cloud Storage

To authenticate either Google Drive or Google Cloud Storage, you just need to run as follow:

#ee_reattach() # reattach ee as a reserve word

# Initialize just Earth Engine
ee_Initialize(email = 'csaybar@gmail.com') # Use the argument email is not mandatory

# Initialize Earth Engine and GD
ee_Initialize(email = 'csaybar@gmail.com', drive = TRUE)

# Initialize Earth Engine and GCS
ee_Initialize(email = 'csaybar@gmail.com', gcs = TRUE)

# Initialize Earth Engine, GD and GCS
ee_Initialize(email = 'csaybar@gmail.com', drive = TRUE, gcs = TRUE)

If the Google account is verified and the permission is granted, you will be directed to an authentication token. Copy this token and paste it in the emerging GUI. Unlike Earth Engine and Google Drive, Google Cloud Storage need to set up its credential manually (link1 and link2). In all cases, the users credentials always will be stored in:

Remember you only have to authorize once, for next sessions it will not be necessary.


The ee_check() function will help you for checking the sanity of your rgee installation and dependencies.