rgee

rgee: An R package for interacting with Google Earth Engine - Published in JOSS (2020)

https://github.com/r-spatial/rgee

Keywords

earth-engine earthengine google-earth-engine googleearthengine r spatial-analysis spatial-data

Scientific Fields

Engineering Computer Science - 60% confidence

Last synced: 4 months ago · JSON representation ·

Repository

Google Earth Engine for R

Basic Info

Host: GitHub
Owner: r-spatial
License: other
Language: R
Default Branch: master
Homepage: https://r-spatial.github.io/rgee/
Size: 31.9 MB

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Stars: 741
Watchers: 38
Forks: 155
Open Issues: 60
Releases: 15

Topics

earth-engine earthengine google-earth-engine googleearthengine r spatial-analysis spatial-data

Created over 6 years ago · Last pushed 4 months ago

Metadata Files

Readme Changelog Contributing License Code of conduct Citation

rgee: Google Earth Engine for R

rgee is an R binding package for calling Google Earth Engine API from within R. Various functions are implemented to simplify the connection with the R spatial ecosystem.

• Installation • Hello World • How does rgee work? • Guides • Contributing • Citation • Credits

What is Google Earth Engine?

Google Earth Engine is a cloud-based platform that enables users to access a petabyte-scale archive of remote sensing data and conduct geospatial analysis on Google's infrastructure. Currently, Google offers support only for Python and JavaScript. rgee fills that gap by providing support for R!. Below, you will find a comparison between the syntax of rgee and the two other client libraries supported by Google.

JS (Code Editor)	Python	R
``` javascript var db = 'CGIAR/SRTM90_V4' var image = ee.Image(db) print(image.bandNames()) #> 'elevation' ```	``` python import ee ee.Initialize(project = "my-project-id") db = 'CGIAR/SRTM90_V4' image = ee.Image(db) image.bandNames().getInfo() #> [u'elevation'] ```	``` r library(rgee) ee_Initialize(project = "my-project-id") db <- 'CGIAR/SRTM90_V4' image <- ee$Image(db) image$bandNames()$getInfo() #> [1] "elevation" ```

Quite similar, isn't it?. However, additional more minor changes should be considered when using Google Earth Engine with R. Please check the consideration section before you start coding!

How to use

NOTE: Create a .Renviron file file to prevent setting RETICULATEPYTHON and EARTHENGINEGCLOUD every time you authenticate/init your account.

``` r library(rgee)

Set your Python ENV

Sys.setenv("RETICULATE_PYTHON" = "/usr/bin/python3")

Set Google Cloud SDK. Only need it the first time you log in.

Sys.setenv("EARTHENGINEGCLOUD" = "home/csaybar/google-cloud-sdk/bin/") eeAuthenticate()

Initialize your Earth Engine Session

ee_Initialize(project = "my-project-id") ```

Earth Engine initialization

You will need to create and register a Google Cloud project to use Earth Engine (via rgee). See the following "Installation" section for instructions. The ID of the Cloud project will need to be supplied to ee_Initialize each time you start a new rgee session. Whenever you see "my-project-id" in rgee example code, replace the string with your specific Cloud project ID. For more information on these topics see about Earth Engine access and authentication and inialization pages.

Installation

Install from CRAN with:

r install.packages("rgee")

Install the development versions from github with

r library(remotes) install_github("r-spatial/rgee")

Furthermore, rgee depends on numpy and earthengine-api and it requires gcloud CLI to authenticate new users. The following example shows how to install and set up 'rgee' on a new Ubuntu computer. If you intend to use rgee on a server, please refer to this example in RStudio Cloud." -- https://posit.cloud/content/5175749)

Create and register a Google Cloud project. Follow the Earth Engine access instructions.

``` r install.packages(c("remotes", "googledrive")) remotes::install_github("r-spatial/rgee")

library(rgee)

Get the username

HOME <- Sys.getenv("HOME")

1. Install miniconda

reticulate::install_miniconda()

2. Install Google Cloud SDK

system("curl -sSL https://sdk.cloud.google.com | bash")

3 Set global parameters

Sys.setenv("RETICULATEPYTHON" = sprintf("%s/.local/share/r-miniconda/bin/python3", HOME)) Sys.setenv("EARTHENGINEGCLOUD" = sprintf("%s/google-cloud-sdk/bin/", HOME))

4 Install rgee Python dependencies

ee_install()

5. Authenticate and initialize your Earth Engine session

Replace "my-project-id" with the ID of the Cloud project you created above

ee_Initialize(project = "my-project-id") ```

There are three (3) different ways to install rgee Python dependencies:

Use ee_install (Highly recommended for users with no experience with Python environments)

r rgee::ee_install()

Use eeinstallset_pyenv (Recommended for users with experience in Python environments)

r rgee::ee_install_set_pyenv( py_path = "/home/csaybar/.virtualenvs/rgee/bin/python", # Change it for your own Python PATH py_env = "rgee" # Change it for your own Python ENV )

Take into account that the Python PATH you set must have earthengine-api and `numpy installed. The use of miniconda/anaconda is mandatory for Windows users, Linux and MacOS users could also use virtualenv. See reticulate documentation for more details.

If you are using MacOS or Linux, you can choose setting the Python PATH directly:

r rgee::ee_install_set_pyenv( py_path = "/usr/bin/python3", py_env = NULL )

However, rgee::eeinstallupgrade and reticulate::py_install will not work until you have set up a Python ENV.

Use the Python PATH setting support that offer Rstudio v.1.4 >. See this tutorial.

After install Python dependencies, you might want to use the function below for checking the rgee status.

r ee_check() # Check non-R dependencies

Sync rgee with other Python packages

Integrate rgee with geemap.

``` r library(reticulate) library(rgee)

1. Initialize the Python Environment

ee_Initialize(project = "my-project-id")

2. Install geemap in the same Python ENV that use rgee

py_install("geemap") gm <- import("geemap") ```

Upgrade the earthengine-api

r library(rgee) ee_Initialize(project = "my-project-id") ee_install_upgrade()

Package Conventions

All rgee functions have the prefix ee_. Auto-completion is your best ally :).
Full access to the Earth Engine API with the prefix ee\$....
Authenticate and Initialize the Earth Engine R API with ee_Initialize. It is necessary once per session!.
rgee is "pipe-friendly"; we re-export %>% but do not require to use it.

Hello World

1. Compute the trend of night-time lights (JS version)

Authenticate and Initialize the Earth Engine R API.

r library(rgee) ee_Initialize(project = "my-project-id")

Let's create a new band containing the image date as years since 1991 by extracting the year of the image acquisition date and subtracting it from 1991.

r createTimeBand <-function(img) { year <- ee$Date(img$get('system:time_start'))$get('year')$subtract(1991L) ee$Image(year)$byte()$addBands(img) }

Use your TimeBand function to map it over the night-time lights collection.

r collection <- ee$ ImageCollection('NOAA/DMSP-OLS/NIGHTTIME_LIGHTS')$ select('stable_lights')$ map(createTimeBand)

Compute a linear fit over the series of values at each pixel, so that you can visualize the y-intercept as green, and the positive/negative slopes as red/blue.

r col_reduce <- collection$reduce(ee$Reducer$linearFit()) col_reduce <- col_reduce$addBands( col_reduce$select('scale')) ee_print(col_reduce)

Let's visualize our map!

r Map$setCenter(9.08203, 47.39835, 3) Map$addLayer( eeObject = col_reduce, visParams = list( bands = c("scale", "offset", "scale"), min = 0, max = c(0.18, 20, -0.18) ), name = "stable lights trend" )

rgee_01

2. Let's play with some precipitation values

Install and load tidyverse and sf R packages, and initialize the Earth Engine R API.

``` r library(tidyverse) library(rgee) library(sf)

ee_Initialize(project = "my-project-id") ```

Read the nc shapefile.

r nc <- st_read(system.file("shape/nc.shp", package = "sf"), quiet = TRUE)

We will use the Terraclimate dataset to extract the monthly precipitation (Pr) from 2001

r terraclimate <- ee$ImageCollection("IDAHO_EPSCOR/TERRACLIMATE") %>% ee$ImageCollection$filterDate("2001-01-01", "2002-01-01") %>% ee$ImageCollection$map(function(x) x$select("pr")) %>% # Select only precipitation bands ee$ImageCollection$toBands() %>% # from imagecollection to image ee$Image$rename(sprintf("PP_%02d",1:12)) # rename the bands of an image

ee_extract will help you to extract monthly precipitation values from the Terraclimate ImageCollection. ee_extract works similar to raster::extract, you just need to define: the ImageCollection object (x), the geometry (y), and a function to summarize the values (fun).

r ee_nc_rain <- ee_extract(x = terraclimate, y = nc["NAME"], sf = FALSE)

Use ggplot2 to generate a beautiful static plot!

r ee_nc_rain %>% pivot_longer(-NAME, names_to = "month", values_to = "pr") %>% mutate(month, month=gsub("PP_", "", month)) %>% ggplot(aes(x = month, y = pr, group = NAME, color = pr)) + geom_line(alpha = 0.4) + xlab("Month") + ylab("Precipitation (mm)") + theme_minimal()

### 3. Create an NDVI-animation (JS version)

Install and load sf. after that, initialize the Earth Engine R API.

``` r library(magick) library(rgee) library(sf)

ee_Initialize(project = "my-project-id") ```

Define the regional bounds of animation frames and a mask to clip the NDVI data by.

r mask <- system.file("shp/arequipa.shp", package = "rgee") %>% st_read(quiet = TRUE) %>% sf_as_ee() region <- mask$geometry()$bounds()

Retrieve the MODIS Terra Vegetation Indices 16-Day Global 1km dataset as an ee.ImageCollection and then, select the NDVI band.

r col <- ee$ImageCollection('MODIS/006/MOD13A2')$select('NDVI')

Group images by composite date

r col <- col$map(function(img) { doy <- ee$Date(img$get('system:time_start'))$getRelative('day', 'year') img$set('doy', doy) }) distinctDOY <- col$filterDate('2013-01-01', '2014-01-01')

Now, let's define a filter that identifies which images from the complete collection match the DOY from the distinct DOY collection.

r filter <- ee$Filter$equals(leftField = 'doy', rightField = 'doy')

Define a join and convert the resulting FeatureCollection to an ImageCollection... it will take you only 2 lines of code!

r join <- ee$Join$saveAll('doy_matches') joinCol <- ee$ImageCollection(join$apply(distinctDOY, col, filter))

Apply median reduction among the matching DOY collections.

r comp <- joinCol$map(function(img) { doyCol = ee$ImageCollection$fromImages( img$get('doy_matches') ) doyCol$reduce(ee$Reducer$median()) })

Almost ready! but let's define RGB visualization parameters first.

r visParams = list( min = 0.0, max = 9000.0, bands = "NDVI_median", palette = c( 'FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718', '74A901', '66A000', '529400', '3E8601', '207401', '056201', '004C00', '023B01', '012E01', '011D01', '011301' ) )

Create RGB visualization images for use as animation frames.

r rgbVis <- comp$map(function(img) { do.call(img$visualize, visParams) %>% ee$Image$clip(mask) })

Let's animate this. Define GIF visualization parameters.

r gifParams <- list( region = region, dimensions = 600, crs = 'EPSG:3857', framesPerSecond = 10 )

Get month names

r dates_modis_mabbr <- distinctDOY %>% ee_get_date_ic %>% # Get Image Collection dates '[['("time_start") %>% # Select time_start column lubridate::month() %>% # Get the month component of the datetime '['(month.abb, .) # subset around month abbreviations

And finally, use eeutilsgif_* functions to render the GIF animation and add some texts.

``` r animation <- eeutilsgifcreator(rgbVis, gifParams, mode = "wb") animation %>% eeutilsgifannotate( text = "NDVI: MODIS/006/MOD13A2", size = 15, color = "white", location = "+10+10" ) %>% eeutilsgifannotate( text = datesmodismabbr, size = 30, location = "+290+350", color = "white", font = "arial", boxcolor = "#000000" ) # -> animationwtxt

eeutilsgifsave(animationwtxt, path = "rasterasee.gif")

```

## How does rgee work?

rgee is not a native Earth Engine API like the Javascript or Python client. Developing an Earth Engine API from scratch would create too much maintenance burden, especially considering that the API is in active development. So, how is it possible to run Earth Engine using R? the answer is [reticulate]! (https://rstudio.github.io/reticulate/). reticulate is an R package designed to allow seamless interoperability between R and Python. When an Earth Engine request is created in R, reticulate will translate this request into Python and pass it to the Earth Engine Python API, which converts the request to a JSON format. Finally, the request is received by the GEE Platform through a Web REST API. The response will follow the same path in reverse.

workflow

Code of Conduct

Please note that the rgee project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Contributing Guide

👍 Thanks for taking the time to contribute! 🎉👍 Please review our Contributing Guide.

Share the love

Enjoying rgee? Let others know about it! Share it on Twitter, LinkedIN or in a blog post to spread the word.

Using rgee for your scientific article? here's how you can cite it

``` r citation("rgee") To cite rgee in publications use:

C Aybar, Q Wu, L Bautista, R Yali and A Barja (2020) rgee: An R package for interacting with Google Earth Engine Journal of Open Source Software URL https://github.com/r-spatial/rgee/.

A BibTeX entry for LaTeX users is

@Article{, title = {rgee: An R package for interacting with Google Earth Engine}, author = {Cesar Aybar and Quisheng Wu and Lesly Bautista and Roy Yali and Antony Barja}, journal = {Journal of Open Source Software}, year = {2020}, } ```

Credits

We want to offer a special thanks :raised_hands: :clap: 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:

Owner

Name: r-spatial
Login: r-spatial
Kind: organization

Website: https://github.com/r-spatial
Repositories: 43
Profile: https://github.com/r-spatial

For packages raster, terra, dismo & geosphere visit the rspatial github organisation (mind the missing '-')

JOSS Publication

rgee: An R package for interacting with Google Earth Engine

Published

July 16, 2020

DOI

10.21105/joss.02272

Volume 5, Issue 51, Page 2272

Authors

Cesar Aybar

Department of Geoinformatics – Z_GIS, University of Salzburg, Austria

Qiusheng Wu

Department of Geography, University of Tennessee, Knoxville, TN 37996, USA

Lesly Bautista

Universidad Nacional Mayor de San Marcos, Lima, Lima 15081, Peru

Roy Yali

Universidad Nacional Mayor de San Marcos, Lima, Lima 15081, Peru

Antony Barja

Universidad Nacional Mayor de San Marcos, Lima, Lima 15081, Peru

Editor

Hugo Ledoux

Citation (CITATION.cff)

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# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "rgee" in publications use:'
type: software
license: Apache-2.0
title: 'rgee: R Bindings for Calling the ''Earth Engine'' API'
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doi: 10.32614/CRAN.package.rgee
identifiers:
- type: url
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abstract: Earth Engine <https://earthengine.google.com/> client library for R. All
  of the 'Earth Engine' API classes, modules, and functions are made available. Additional
  functions implemented include importing (exporting) of Earth Engine spatial objects,
  extraction of time series, interactive map display, assets management interface,
  and metadata display. See <https://r-spatial.github.io/rgee/> for further details.
authors:
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    email: kevin@posit.co
  - family-names: Allaire
    given-names: JJ
    email: jj@posit.co
  - family-names: Tang
    given-names: Yuan
    email: terrytangyuan@gmail.com
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    given-names: Kevin
    email: kevin@rstudio.com
  - family-names: Allaire
    given-names: JJ
    email: jj@posit.co
  - family-names: Wickham
    given-names: Hadley
    email: hadley@posit.co
  - family-names: Ritchie
    given-names: Gary
    email: gary@posit.co
  year: '2025'
  doi: 10.32614/CRAN.package.rstudioapi
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- type: software
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  abstract: 'leaflet: Create Interactive Web Maps with the JavaScript ''Leaflet''
    Library'
  notes: Imports
  url: https://rstudio.github.io/leaflet/
  repository: https://CRAN.R-project.org/package=leaflet
  authors:
  - family-names: Cheng
    given-names: Joe
    email: joe@posit.co
  - family-names: Schloerke
    given-names: Barret
    email: barret@posit.co
    orcid: https://orcid.org/0000-0001-9986-114X
  - family-names: Karambelkar
    given-names: Bhaskar
  - family-names: Xie
    given-names: Yihui
  year: '2025'
  doi: 10.32614/CRAN.package.leaflet
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  title: magrittr
  abstract: 'magrittr: A Forward-Pipe Operator for R'
  notes: Imports
  url: https://magrittr.tidyverse.org
  repository: https://CRAN.R-project.org/package=magrittr
  authors:
  - family-names: Bache
    given-names: Stefan Milton
    email: stefan@stefanbache.dk
  - family-names: Wickham
    given-names: Hadley
    email: hadley@rstudio.com
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  abstract: 'jsonlite: A Simple and Robust JSON Parser and Generator for R'
  notes: Imports
  url: https://jeroen.r-universe.dev/jsonlite
  repository: https://CRAN.R-project.org/package=jsonlite
  authors:
  - family-names: Ooms
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    email: csardi.gabor@gmail.com
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  - family-names: Chang
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  - family-names: D'Agostino McGowan
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  - family-names: Wickham
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    email: hadley@posit.co
    orcid: https://orcid.org/0000-0003-4757-117X
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Create event: 1

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Total Committers: 22
Avg Commits per committer: 57.955
Development Distribution Score (DDS): 0.433

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Commits: 131
Committers: 5
Avg Commits per committer: 26.2
Development Distribution Score (DDS): 0.092

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Cesar Luis Aybar Camacho	a**4@g**m	723
GitHub Action	a**n@g**m	438
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Roy Yali Samaniego	r**3@g**m	17
Matthieu Stigler	M**r@g**m	15
valeriallactayo	v**o@u**e	14
gcarrascoe	g**1@g**m	12
Jacob B. Socolar	j**r@g**m	12
Marouf Shaikh	m**8@g**m	2
Justin Braaten	j****e	2
Daniel Bonnéry	d**y@g**m	1
Hugo Ledoux	h**x@t**l	1
Keisuke ANDO	a**o@m**p	1
LBautistaB13	5****3	1
Martin Holdrege	m**e@g**m	1
Nils	r**a@z**h	1
Paul Frater	p**r@g**m	1
runner	r**r@M**l	1
runner	r**r@M**l	1
runner	r**r@M**l	1
runner	r**r@M**l	1
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Total pull requests: 25
Average time to close issues: 3 months
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Total pull request authors: 11
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Average comments per pull request: 0.84
Merged pull requests: 18
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Bot pull requests: 0

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Pull requests: 11
Average time to close issues: 11 days
Average time to close pull requests: 14 days
Issue authors: 14
Pull request authors: 4
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Average comments per pull request: 0.18
Merged pull requests: 8
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Total downloads:
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Total docker downloads: 21,622

Total dependent packages: 3
(may contain duplicates)
Total dependent repositories: 13
(may contain duplicates)
Total versions: 13
Total maintainers: 1

cran.r-project.org: rgee

R Bindings for Calling the 'Earth Engine' API

Homepage: https://github.com/r-spatial/rgee/
Documentation: http://cran.r-project.org/web/packages/rgee/rgee.pdf
License: Apache License (≥ 2.0)
Latest release: 1.1.7
published about 2 years ago

Versions: 8
Dependent Packages: 3
Dependent Repositories: 13
Downloads: 1,688 Last month
Docker Downloads: 21,622

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Forks count: 0.4%

Stargazers count: 0.6%

Docker downloads count: 6.4%

Average: 6.7%

Dependent repos count: 8.1%

Downloads: 11.5%

Dependent packages count: 13.3%

Maintainers (1)

csaybar@gmail.com

Last synced: 4 months ago

conda-forge.org: r-rgee

Homepage: https://github.com/r-spatial/rgee/, https://r-spatial.github.io/rgee/, https://github.com/google/earthengine-api/
License: Apache-2.0
Latest release: 1.1.5
published over 3 years ago

Versions: 5
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Forks count: 14.5%

Stargazers count: 16.2%

Average: 29.0%

Dependent repos count: 34.0%

Dependent packages count: 51.2%

Last synced: 4 months ago

rgee

Science Score: 100.0%

Keywords

Scientific Fields

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

rgee: Google Earth Engine for R

rgee is an R binding package for calling Google Earth Engine API from within R. Various functions are implemented to simplify the connection with the R spatial ecosystem.

What is Google Earth Engine?

How to use

Set your Python ENV

Set Google Cloud SDK. Only need it the first time you log in.

Initialize your Earth Engine Session

Earth Engine initialization

Installation

Get the username

1. Install miniconda

2. Install Google Cloud SDK

3 Set global parameters

4 Install rgee Python dependencies

5. Authenticate and initialize your Earth Engine session

Replace "my-project-id" with the ID of the Cloud project you created above

Sync rgee with other Python packages

1. Initialize the Python Environment

2. Install geemap in the same Python ENV that use rgee

Package Conventions

Hello World

1. Compute the trend of night-time lights (JS version)

2. Let's play with some precipitation values

eeutilsgifsave(animationwtxt, path = "rasterasee.gif")

Code of Conduct

Contributing Guide

Share the love

Credits

Owner

JOSS Publication

rgee: An R package for interacting with Google Earth Engine

Authors

Editor

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Citation (CITATION.cff)

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conda-forge.org: r-rgee

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