rgee: An R package for interacting with Google Earth Engine

Google Earth Engine (Gorelick et al., 2017) is a cloud computing platform designed for planetary-scale environmental data analysis that only can be accessed via the Earth Engine code editor, third-party web apps, and the JavaScript and Python client libraries. rgee is a non-official client library for R that uses reticulate to wrap the Earth Engine Python API and provide R users with a familiar interface, rapid development features, and flexibility to analyze data using open-source, R third-party packages.

Details

The package implements and supports:

Earth Engine Module
Install or set all rgee dependencies
Check non-R dependencies
Clean non-R dependencies
Session management
Transform an R Date to an EE Date or vice versa
Create Interactive visualization Maps
Image download
Vector download
Generic download
Assets management
Upload raster
Upload vector
Upload generic
Extract values
Helper functions
Utils functions

I. Earth Engine Module

Interface to main Earth Engine module. Provides access to top level classes and functions as well as sub-modules (e.g. ee$Image, ee$FeatureCollection$first, etc.).

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`ee`	Main Earth Engine module.
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II. Install or set non-R rgee dependencies

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`ee_install`	Create an isolated Python virtual environment with all rgee dependencies.
`ee_install_set_pyenv`	Configure which version of Python to use with rgee.
`ee_install_upgrade`	Upgrade the Earth Engine Python API.
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III. Check non-R dependencies

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`ee_check`	Check all non-R dependencies.
`ee_check_python`	Check Python environment.
`ee_check_credentials`	Check Google credentials.
`ee_check_python_packages`	Check Python packages: earthengine-api and numpy.
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IV. Clean container, credentials, or rgee system variables

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`ee_clean_container`	Delete files from either a Folder or a Bucket.
`ee_clean_pyenv`	Remove rgee system variables from .Renviron.
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V. Session management

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`ee_Initialize`	Authenticate and Initialize Earth Engine.
`ee_version`	Earth Engine API version.
`ee_user_info`	Display the credentials and general info of the initialized user.
`ee_users`	Display the credentials of all users as a table.
`ee_get_assethome`	Get the Asset home name.
`ee_get_earthengine_path`	Get the path where the credentials are stored.
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VII. Transform an R Date to an EE Date or vice versa

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`eedate_to_rdate`	Pass an Earth Engine date object to R.
`rdate_to_eedate`	Pass an R date object to Earth Engine.
`ee_get_date_img`	Get the date of a EE Image.
`ee_get_date_ic`	Get the date of a EE ImageCollection.
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VIII. Visualization Map

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`Map`	R6 object (Map) to display Earth Engine (EE) spatial objects.
`R6Map`	R6 class to display Earth Engine (EE) spatial objects.
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IX. Image download

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`ee_as_raster`	Convert an Earth Engine (EE) image in a raster object.
`ee_as_stars`	Convert an Earth Engine (EE) image in a stars object.
`ee_as_thumbnail`	Create an R spatial gridded object from an EE thumbnail image.
`ee_image_to_asset`	Creates a task to export an EE Image to their EE Assets.
`ee_image_to_drive`	Creates a task to export an EE Image to Drive.
`ee_image_to_gcs`	Creates a task to export an EE Image to Google Cloud Storage.
`ee_image_info`	Approximate size of an EE Image object.
`ee_imagecollection_to_local`	Save an EE ImageCollection in their local system.
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X. Vector download

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`ee_as_sf`	Convert an Earth Engine table in an sf object.
`ee_table_to_asset`	Creates a task to export a FeatureCollection to an EE table asset.
`ee_table_to_drive`	Creates a task to export a FeatureCollection to Google Drive.
`ee_table_to_gcs`	Creates a task to export a FeatureCollection to Google Cloud Storage.
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XI. Generic download

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`ee_drive_to_local`	Move results from Google Drive to a local directory.
`ee_gcs_to_local`	Move results from Google Cloud Storage to a local directory.
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XII. Assets management

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`ee_manage-tools`	Interface to manage the Earth Engine Asset.
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XIII. Upload raster

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`stars_as_ee`	Convert a stars or stars-proxy object into an EE Image object.
`raster_as_ee`	Convert a Raster* object into an EE Image object.
`gcs_to_ee_image`	Move a GeoTIFF image from GCS to their EE assets.
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XIV. Upload vector

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`gcs_to_ee_table`	Move a zipped shapefile from GCS to their EE Assets.
`sf_as_ee`	Convert an sf object to an EE object.
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XV. Upload generic

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`local_to_gcs`	Upload local files to Google Cloud Storage.
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XVI. Extract values

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`ee_extract`	Extract values from EE Images or ImageCollections objects.
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XVII. Helper functions

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`ee_help`	Documentation for Earth Engine Objects.
`ee_print`	Print and return metadata about Spatial Earth Engine Objects.
`ee_monitoring`	Monitoring Earth Engine task progress.
`print`	Print Earth Engine objects.
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XVIII. Utils functions

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`ee_utils_py_to_r`	Convert between Python and R objects.
`ee_utils_pyfunc`	Wrap an R function in a Python function with the same signature.
`ee_utils_shp_to_zip`	Create a zip file from an sf object.
`ee_utils_create_json`	Convert a R list into a JSON file.
`ee_utils_create_manifest_image`	Create a manifest to upload an image.
`ee_utils_create_manifest_table`	Create a manifest to upload a table.
`ee_utils_get_crs`	Convert EPSG, ESRI or SR-ORG code into a OGC WKT.
`ee_utils_future_value`	The value of a future or the values of all elements in a container.
`ee_utils_dataset_display`	Search into the Earth Engine Data Catalog.
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Acknowledgments

We want to offer a special thanks to Justin Braaten for his wise and helpful comments in the whole development of rgee. As well, we would like to mention the following third-party R/Python packages for contributing indirectly to the improvement of rgee:

gee_asset_manager - Lukasz Tracewski
geeup - Samapriya Roy
geeadd - Samapriya Roy
eemont - David Montero Loaiza
cartoee - Kel Markert
geetools - Rodrigo E. Principe
landsat-extract-gee - Loïc Dutrieux
earthEngineGrabR - JesJehle
sf - Edzer Pebesma
stars - Edzer Pebesma
gdalcubes - Marius Appel

Author

Maintainer: Cesar Aybar csaybar@gmail.com (ORCID)

Other contributors:

Wu Qiusheng giswqs@gmail.com (ORCID) [contributor]
Lesly Bautista leslyarcelly.213@gmail.com (ORCID) [contributor]
Roy Yali ryali93@gmail.com (ORCID) [contributor]
Antony Barja antony.barja8@gmail.com (ORCID) [contributor]
Kevin Ushey kevin@rstudio.com [contributor]
Jeroen Ooms jeroen@berkeley.edu (ORCID) [contributor]
Tim Appelhans tim.appelhans@gmail.com [contributor]
JJ Allaire jj@rstudio.com [contributor]
Yuan Tang terrytangyuan@gmail.com [contributor]
Samapriya Roy samapriya.roy@gmail.com [contributor]
MariaElena Adauto 2a.mariaelena@gmail.com (ORCID) [contributor]
Gabriel Carrasco gabriel.carrasco@upch.pe (ORCID) [contributor]
Henrik Bengtsson henrikb@braju.com [contributor]
Jeffrey Hollister hollister.jeff@epa.gov (Hollister reviewed the package for JOSS, see https://github.com/openjournals/joss-reviews/issues/2272/) [reviewer]
Gennadii Donchyts (Gena reviewed the package for JOSS, see https://github.com/openjournals/joss-reviews/issues/2272/) [reviewer]
Marius Appel marius.appel@uni-muenster.de (Appel reviewed the package for JOSS, see https://github.com/openjournals/joss-reviews/issues/2272/) [reviewer]