rgee

An R binding package for calling Google Earth Engine API from within R.
https://github.com/r-spatial/rgee

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

Last synced: about 22 hours ago
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Repository metadata

Google Earth Engine for R

• Host: GitHub
• URL: https://github.com/r-spatial/rgee
• Owner: r-spatial
• License: other
• Created: 2019-09-03T05:38:52.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2024-05-09T16:20:50.000Z (1 day ago)
• Last Synced: 2024-05-10T07:04:38.959Z (1 day ago)
• Topics: earth-engine, earthengine, google-earth-engine, googleearthengine, r, spatial-analysis, spatial-data
• Language: R
• Homepage: https://r-spatial.github.io/rgee/
• Size: 31.4 MB
• Stars: 635
• Watchers: 40
• Forks: 142
• Open Issues: 43
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.md
  • Code of conduct: CODE_OF_CONDUCT.md
  • Citation: CITATION.cff

README

        


  


  

  

  

  


  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](https://earthengine.google.com/) 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()

db = 'CGIAR/SRTM90_V4'

image = ee.Image(db)

image.bandNames().getInfo()

#> [u'elevation']

```

``` r

library(rgee)

ee_Initialize()

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](https://r-spatial.github.io/rgee/articles/rgee02.html) before you start coding!

## How to use

**NOTE: Create a [.Renviron file](https://cran.r-project.org/web/packages/startup/vignettes/startup-intro.html) file to prevent setting RETICULATE_PYTHON and EARTHENGINE_GCLOUD 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("EARTHENGINE_GCLOUD" = "home/csaybar/google-cloud-sdk/bin/")

ee_Authenticate()

# Init your Earth Session  

ee_Initialize()

```

## 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](https://pypi.org/project/numpy/) and [earthengine-api](https://pypi.org/project/earthengine-api/) and it requires **[gcloud CLI](https://cloud.google.com/sdk/docs/install#deb)** 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)

``` 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("RETICULATE_PYTHON" = sprintf("%s/.local/share/r-miniconda/bin/python3", HOME))

Sys.setenv("EARTHENGINE_GCLOUD" = sprintf("%s/google-cloud-sdk/bin/", HOME))

# 4 Install rgee Python dependencies

ee_install()

# 5. Authenticate and init your EE session

ee_Initialize()

```

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

1.  Use [**ee_install**](https://r-spatial.github.io/rgee/reference/ee_install.html) (Highly recommended for users with no experience with Python environments)

``` r

rgee::ee_install()

```

2.  Use [**ee_install_set_pyenv**](https://r-spatial.github.io/rgee/reference/ee_install_set_pyenv.html) (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](https://rstudio.github.io/reticulate/articles/python_packages.html) 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::ee_install_upgrade**](https://r-spatial.github.io/rgee/reference/ee_install_upgrade.html) and [**reticulate::py_install**](https://rstudio.github.io/reticulate/reference/py_install.html) will not work until you have set up a Python ENV.

3.  Use the Python PATH setting support that offer [Rstudio v.1.4 \>](https://blog.rstudio.com/2020/10/07/rstudio-v1-4-preview-python-support/). See this [tutorial](https://github.com/r-spatial/rgee/tree/help/rstudio/).

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](https://r-spatial.github.io/rgee/) with [geemap](https://geemap.org/).

``` r

library(reticulate)

library(rgee)

# 1. Initialize the Python Environment

ee_Initialize()

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

py_install("geemap")

gm <- import("geemap")

```

Upgrade the [earthengine-api](https://pypi.org/project/earthengine-api/)

``` r

library(rgee)

ee_Initialize()

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\$...**](https://developers.google.com/earth-engine/).

-   Authenticate and Initialize the Earth Engine R API with [**ee_Initialize**](https://r-spatial.github.io/rgee/reference/ee_Initialize.html). 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](https://github.com/google/earthengine-api/))

Authenticate and Initialize the Earth Engine R API.

``` r

library(rgee)

ee_Initialize()

```

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](https://developers.google.com/earth-engine/datasets/catalog/NOAA_DMSP-OLS_NIGHTTIME_LIGHTS/).

``` 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](https://user-images.githubusercontent.com/16768318/71565699-51e4a500-2aa9-11ea-83c3-9e1d32c82ba6.png)

### 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()

```

Read the `nc` shapefile.

``` r

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

```

We will use the [Terraclimate dataset](https://developers.google.com/earth-engine/datasets/catalog/IDAHO_EPSCOR_TERRACLIMATE/) 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](https://developers.google.com/earth-engine/tutorials/community/modis-ndvi-time-series-animation/))

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

``` r

library(magick)

library(rgee)

library(sf)

ee_Initialize()

```

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 ee_utils_gif\_\* functions to render the GIF animation and add some texts.

``` r

animation <- ee_utils_gif_creator(rgbVis, gifParams, mode = "wb")

animation %>%

  ee_utils_gif_annotate(

    text = "NDVI: MODIS/006/MOD13A2",

    size = 15, color = "white",

    location = "+10+10"

  ) %>%

  ee_utils_gif_annotate(

    text = dates_modis_mabbr,

    size = 30,

    location = "+290+350",

    color = "white",

    font = "arial",

    boxcolor = "#000000"

  ) # -> animation_wtxt

# ee_utils_gif_save(animation_wtxt, path = "raster_as_ee.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](https://github.com/google/earthengine-api). 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](https://user-images.githubusercontent.com/16768318/71569603-3341d680-2ac8-11ea-8787-4dd1fbba326f.png)

## Code of Conduct

  Please note that the `rgee` project is released with a [Contributor Code of Conduct](CODE_OF_CONDUCT.md). 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](CONTRIBUTING.md).

## 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**](https://github.com/jdbcode) 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**](https://github.com/tracek/gee_asset_manager/)

-   [**geeup - Samapriya Roy**](https://github.com/samapriya/geeup/)

-   [**geeadd - Samapriya Roy**](https://github.com/samapriya/gee_asset_manager_addon/)

-   [**cartoee - Kel Markert**](https://github.com/KMarkert/cartoee/)

-   [**geetools - Rodrigo E. Principe**](https://github.com/gee-community/gee_tools/)

-   [**landsat-extract-gee - Loïc Dutrieux**](https://github.com/loicdtx/landsat-extract-gee/)

-   [**earthEngineGrabR - JesJehle**](https://github.com/JesJehle/earthEngineGrabR/)

-   [**sf - Edzer Pebesma**](https://github.com/r-spatial/sf/)

-   [**stars - Edzer Pebesma**](https://github.com/r-spatial/stars/)

-   [**gdalcubes - Marius Appel**](https://github.com/appelmar/gdalcubes/)

      

Citation (CITATION.cff)

# -----------------------------------------------------------
# CITATION file created with {cffr} R package, v0.5.0
# 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'
version: 1.1.7
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:
- family-names: Aybar
  given-names: Cesar
  email: [email protected]
  orcid: https://orcid.org/0000-0003-2745-9535
repository: https://CRAN.R-project.org/package=rgee
repository-code: https://github.com/r-spatial/rgee/issues/
url: https://github.com/r-spatial/rgee/
contact:
- family-names: Aybar
  given-names: Cesar
  email: [email protected]
  orcid: https://orcid.org/0000-0003-2745-9535
references:
- type: software
  title: 'R: A Language and Environment for Statistical Computing'
  notes: Depends
  url: https://www.R-project.org/
  authors:
  - name: R Core Team
  location:
    name: Vienna, Austria
  year: '2023'
  institution:
    name: R Foundation for Statistical Computing
  version: '>= 3.3.0'
- type: software
  title: methods
  abstract: 'R: A Language and Environment for Statistical Computing'
  notes: Imports
  authors:
  - name: R Core Team
  location:
    name: Vienna, Austria
  year: '2023'
  institution:
    name: R Foundation for Statistical Computing
- type: software
  title: reticulate
  abstract: 'reticulate: Interface to ''Python'''
  notes: Imports
  url: https://rstudio.github.io/reticulate/
  repository: https://CRAN.R-project.org/package=reticulate
  authors:
  - family-names: Ushey
    given-names: Kevin
    email: [email protected]
  - family-names: Allaire
    given-names: JJ
    email: [email protected]
  - family-names: Tang
    given-names: Yuan
    email: [email protected]
    orcid: https://orcid.org/0000-0001-5243-233X
  year: '2023'
  version: '>= 1.27'
- type: software
  title: rstudioapi
  abstract: 'rstudioapi: Safely Access the RStudio API'
  notes: Imports
  url: https://rstudio.github.io/rstudioapi/
  repository: https://CRAN.R-project.org/package=rstudioapi
  authors:
  - family-names: Ushey
    given-names: Kevin
    email: [email protected]
  - family-names: Allaire
    given-names: JJ
    email: [email protected]
  - family-names: Wickham
    given-names: Hadley
    email: [email protected]
  - family-names: Ritchie
    given-names: Gary
    email: [email protected]
  year: '2023'
  version: '>= 0.7'
- type: software
  title: leaflet
  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: [email protected]
  - family-names: Schloerke
    given-names: Barret
    email: [email protected]
    orcid: https://orcid.org/0000-0001-9986-114X
  - family-names: Karambelkar
    given-names: Bhaskar
  - family-names: Xie
    given-names: Yihui
  year: '2023'
  version: '>= 2.0.2'
- type: software
  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: [email protected]
  - family-names: Wickham
    given-names: Hadley
    email: [email protected]
  year: '2023'
- type: software
  title: jsonlite
  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
    given-names: Jeroen
    email: [email protected]
    orcid: https://orcid.org/0000-0002-4035-0289
  year: '2023'
- type: software
  title: processx
  abstract: 'processx: Execute and Control System Processes'
  notes: Imports
  url: https://processx.r-lib.org
  repository: https://CRAN.R-project.org/package=processx
  authors:
  - family-names: Csárdi
    given-names: Gábor
    email: [email protected]
    orcid: https://orcid.org/0000-0001-7098-9676
  - family-names: Chang
    given-names: Winston
  year: '2023'
- type: software
  title: leafem
  abstract: 'leafem: ''leaflet'' Extensions for ''mapview'''
  notes: Imports
  url: https://r-spatial.github.io/leafem/
  repository: https://CRAN.R-project.org/package=leafem
  authors:
  - family-names: Appelhans
    given-names: Tim
    email: [email protected]
  year: '2023'
- type: software
  title: crayon
  abstract: 'crayon: Colored Terminal Output'
  notes: Imports
  url: https://github.com/r-lib/crayon#readme
  repository: https://CRAN.R-project.org/package=crayon
  authors:
  - family-names: Csárdi
    given-names: Gábor
    email: [email protected]
  year: '2023'
- type: software
  title: R6
  abstract: 'R6: Encapsulated Classes with Reference Semantics'
  notes: Imports
  url: https://r6.r-lib.org
  repository: https://CRAN.R-project.org/package=R6
  authors:
  - family-names: Chang
    given-names: Winston
    email: [email protected]
  year: '2023'
- type: software
  title: cli
  abstract: 'cli: Helpers for Developing Command Line Interfaces'
  notes: Imports
  url: https://cli.r-lib.org
  repository: https://CRAN.R-project.org/package=cli
  authors:
  - family-names: Csárdi
    given-names: Gábor
    email: [email protected]
  year: '2023'
- type: software
  title: magick
  abstract: 'magick: Advanced Graphics and Image-Processing in R'
  notes: Suggests
  url: https://docs.ropensci.org/magick/
  repository: https://CRAN.R-project.org/package=magick
  authors:
  - family-names: Ooms
    given-names: Jeroen
    email: [email protected]
    orcid: https://orcid.org/0000-0002-4035-0289
  year: '2023'
- type: software
  title: geojsonio
  abstract: 'geojsonio: Convert Data from and to ''GeoJSON'' or ''TopoJSON'''
  notes: Suggests
  url: https://docs.ropensci.org/geojsonio/
  repository: https://CRAN.R-project.org/package=geojsonio
  authors:
  - family-names: Chamberlain
    given-names: Scott
    email: [email protected]
  - family-names: Teucher
    given-names: Andy
    email: [email protected]
  - family-names: Mahoney
    given-names: Michael
    email: [email protected]
    orcid: https://orcid.org/0000-0003-2402-304X
  year: '2023'
- type: software
  title: sf
  abstract: 'sf: Simple Features for R'
  notes: Suggests
  url: https://r-spatial.github.io/sf/
  repository: https://CRAN.R-project.org/package=sf
  authors:
  - family-names: Pebesma
    given-names: Edzer
    email: [email protected]
    orcid: https://orcid.org/0000-0001-8049-7069
  year: '2023'
- type: software
  title: stars
  abstract: 'stars: Spatiotemporal Arrays, Raster and Vector Data Cubes'
  notes: Suggests
  url: https://r-spatial.github.io/stars/
  repository: https://CRAN.R-project.org/package=stars
  authors:
  - family-names: Pebesma
    given-names: Edzer
    email: [email protected]
    orcid: https://orcid.org/0000-0001-8049-7069
  year: '2023'
- type: software
  title: googledrive
  abstract: 'googledrive: An Interface to Google Drive'
  notes: Suggests
  url: https://googledrive.tidyverse.org
  repository: https://CRAN.R-project.org/package=googledrive
  authors:
  - family-names: D'Agostino McGowan
    given-names: Lucy
  - family-names: Bryan
    given-names: Jennifer
    email: [email protected]
    orcid: https://orcid.org/0000-0002-6983-2759
  year: '2023'
  version: '>= 2.0.0'
- type: software
  title: gargle
  abstract: 'gargle: Utilities for Working with Google APIs'
  notes: Suggests
  url: https://gargle.r-lib.org
  repository: https://CRAN.R-project.org/package=gargle
  authors:
  - family-names: Bryan
    given-names: Jennifer
    email: [email protected]
    orcid: https://orcid.org/0000-0002-6983-2759
  - family-names: Citro
    given-names: Craig
    email: [email protected]
  - family-names: Wickham
    given-names: Hadley
    email: [email protected]
    orcid: https://orcid.org/0000-0003-4757-117X
  year: '2023'
- type: software
  title: httr
  abstract: 'httr: Tools for Working with URLs and HTTP'
  notes: Suggests
  url: https://httr.r-lib.org/
  repository: https://CRAN.R-project.org/package=httr
  authors:
  - family-names: Wickham
    given-names: Hadley
    email: [email protected]
  year: '2023'
- type: software
  title: digest
  abstract: 'digest: Create Compact Hash Digests of R Objects'
  notes: Suggests
  url: https://dirk.eddelbuettel.com/code/digest.html
  repository: https://CRAN.R-project.org/package=digest
  authors:
  - family-names: Lucas
    given-names: Dirk Eddelbuettel with contributions by Antoine
    email: [email protected]
  - family-names: Tuszynski
    given-names: Jarek
  - family-names: Bengtsson
    given-names: Henrik
  - family-names: Urbanek
    given-names: Simon
  - family-names: Frasca
    given-names: Mario
  - family-names: Lewis
    given-names: Bryan
  - family-names: Stokely
    given-names: Murray
  - family-names: Muehleisen
    given-names: Hannes
  - family-names: Murdoch
    given-names: Duncan
  - family-names: Hester
    given-names: Jim
  - family-names: Wu
    given-names: Wush
  - family-names: Kou
    given-names: Qiang
  - family-names: Onkelinx
    given-names: Thierry
  - family-names: Lang
    given-names: Michel
  - family-names: Simko
    given-names: Viliam
  - family-names: Hornik
    given-names: Kurt
  - family-names: Neal
    given-names: Radford
  - family-names: Bell
    given-names: Kendon
  - family-names: de Queljoe
    given-names: Matthew
  - family-names: Suruceanu
    given-names: Ion
  - family-names: Denney
    given-names: Bill
  - family-names: Schumacher
    given-names: Dirk
  - family-names: Chang
    given-names: Winston
  - family-names: Attali.
    given-names: Dean
  year: '2023'
- type: software
  title: testthat
  abstract: 'testthat: Unit Testing for R'
  notes: Suggests
  url: https://testthat.r-lib.org
  repository: https://CRAN.R-project.org/package=testthat
  authors:
  - family-names: Wickham
    given-names: Hadley
    email: [email protected]
  year: '2023'
- type: software
  title: future
  abstract: 'future: Unified Parallel and Distributed Processing in R for Everyone'
  notes: Suggests
  url: https://future.futureverse.org
  repository: https://CRAN.R-project.org/package=future
  authors:
  - family-names: Bengtsson
    given-names: Henrik
    email: [email protected]
  year: '2023'
- type: software
  title: terra
  abstract: 'terra: Spatial Data Analysis'
  notes: Suggests
  url: https://rspatial.org/
  repository: https://CRAN.R-project.org/package=terra
  authors:
  - family-names: Hijmans
    given-names: Robert J.
    email: [email protected]
    orcid: https://orcid.org/0000-0001-5872-2872
  year: '2023'
- type: software
  title: covr
  abstract: 'covr: Test Coverage for Packages'
  notes: Suggests
  url: https://covr.r-lib.org
  repository: https://CRAN.R-project.org/package=covr
  authors:
  - family-names: Hester
    given-names: Jim
    email: [email protected]
  year: '2023'
- type: software
  title: knitr
  abstract: 'knitr: A General-Purpose Package for Dynamic Report Generation in R'
  notes: Suggests
  url: https://yihui.org/knitr/
  repository: https://CRAN.R-project.org/package=knitr
  authors:
  - family-names: Xie
    given-names: Yihui
    email: [email protected]
    orcid: https://orcid.org/0000-0003-0645-5666
  year: '2023'
- type: software
  title: rmarkdown
  abstract: 'rmarkdown: Dynamic Documents for R'
  notes: Suggests
  url: https://pkgs.rstudio.com/rmarkdown/
  repository: https://CRAN.R-project.org/package=rmarkdown
  authors:
  - family-names: Allaire
    given-names: JJ
    email: [email protected]
  - family-names: Xie
    given-names: Yihui
    email: [email protected]
    orcid: https://orcid.org/0000-0003-0645-5666
  - family-names: Dervieux
    given-names: Christophe
    email: [email protected]
    orcid: https://orcid.org/0000-0003-4474-2498
  - family-names: McPherson
    given-names: Jonathan
    email: [email protected]
  - family-names: Luraschi
    given-names: Javier
  - family-names: Ushey
    given-names: Kevin
    email: [email protected]
  - family-names: Atkins
    given-names: Aron
    email: [email protected]
  - family-names: Wickham
    given-names: Hadley
    email: [email protected]
  - family-names: Cheng
    given-names: Joe
    email: [email protected]
  - family-names: Chang
    given-names: Winston
    email: [email protected]
  - family-names: Iannone
    given-names: Richard
    email: [email protected]
    orcid: https://orcid.org/0000-0003-3925-190X
  year: '2023'
- type: software
  title: png
  abstract: 'png: Read and write PNG images'
  notes: Suggests
  url: http://www.rforge.net/png/
  repository: https://CRAN.R-project.org/package=png
  authors:
  - family-names: Urbanek
    given-names: Simon
    email: [email protected]
  year: '2023'
- type: software
  title: googleCloudStorageR
  abstract: 'googleCloudStorageR: Interface with Google Cloud Storage API'
  notes: Suggests
  url: https://code.markedmondson.me/googleCloudStorageR/
  repository: https://CRAN.R-project.org/package=googleCloudStorageR
  authors:
  - family-names: Edmondson
    given-names: Mark
    email: [email protected]
    orcid: https://orcid.org/0000-0002-8434-3881
  year: '2023'
- type: software
  title: leaflet.extras2
  abstract: 'leaflet.extras2: Extra Functionality for ''leaflet'' Package'
  notes: Suggests
  url: https://trafficonese.github.io/leaflet.extras2/
  repository: https://CRAN.R-project.org/package=leaflet.extras2
  authors:
  - family-names: Sebastian
    given-names: Gatscha
    email: [email protected]
  year: '2023'
- type: software
  title: spelling
  abstract: 'spelling: Tools for Spell Checking in R'
  notes: Suggests
  url: https://docs.ropensci.org/spelling/
  repository: https://CRAN.R-project.org/package=spelling
  authors:
  - family-names: Ooms
    given-names: Jeroen
    email: [email protected]
    orcid: https://orcid.org/0000-0002-4035-0289
  - family-names: Hester
    given-names: Jim
    email: [email protected]
  year: '2023'
- type: software
  title: raster
  abstract: 'raster: Geographic Data Analysis and Modeling'
  notes: Suggests
  url: https://rspatial.org/raster
  repository: https://CRAN.R-project.org/package=raster
  authors:
  - family-names: Hijmans
    given-names: Robert J.
    email: [email protected]
    orcid: https://orcid.org/0000-0001-5872-2872
  year: '2023'
identifiers:
- type: url
  value: https://r-spatial.github.io/rgee/
- type: url
  value: https://github.com/google/earthengine-api/

---

Owner metadata

• Name: r-spatial
• Login: r-spatial
• Email:
• Kind: organization
• Description: For packages raster, terra, dismo & geosphere visit the rspatial github organisation (mind the missing '-')
• Website: https://github.com/r-spatial
• Location:
• Twitter:
• Company:
• Icon url: https://avatars.githubusercontent.com/u/25086656?v=4
• Repositories: 43
• Last ynced at: 2024-03-25T20:58:38.397Z
• Profile URL: https://github.com/r-spatial

---

GitHub Events

Total

• Create event: 29
• Release event: 12
• Issues event: 477
• Watch event: 549
• Delete event: 2
• Issue comment event: 951
• Push event: 722
• Pull request review event: 4
• Pull request event: 55
• Fork event: 138

Last Year

• Create event: 1
• Fork event: 12
• Issue comment event: 99
• Issues event: 41
• Pull request event: 11
• Pull request review event: 2
• Push event: 63
• Watch event: 88

---

Committers metadata

Last synced: 1 day ago

Name	Email	Commits
Cesar Luis Aybar Camacho	a****4@g****m	440
GitHub Action	a****n@g****m	286
csaybar	c****r@g****m	283
Roy Yali Samaniego	r****3@g****m	17
gcarrascoe	g****1@g****m	12
Jacob B. Socolar	j****r@g****m	12
valeriallactayo	v****o@u****e	11
ambarja	a****8@g****m	8
Matthieu Stigler	M****r@g****m	7
valeriallactayo	7****o	3
Daniel Bonnéry	d****y@g****m	1
Hugo Ledoux	h****x@t****l	1
Martin Holdrege	m****e@g****m	1
Paul Frater	p****r@g****m	1
egbendito	e****o@g****m	1
runner	r****r@M****l	1
runner	r****r@M****l	1
ambarja	a****a	1
Nils	r****a@z****h	1
LBautistaB13	5****3	1
runner	r****r@M****l	1
runner	r****r@M****l	1

Committer domains:

• zhaw.ch: 1
• tudelft.nl: 1
• unmsm.edu.pe: 1
• github.com: 1

---

Issue and Pull Request metadata

Last synced: 2 days ago

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/r-spatial/rgee

---

---

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Package metadata

• Total packages: 2
• Total downloads:
  • cran: 1,664 last-month
• Total docker downloads: 7
• Total dependent packages: 3 (may contain duplicates)
• Total dependent repositories: 13 (may contain duplicates)
• Total versions: 13
• Total maintainers: 1

---

Dependencies

Score: 17.04208165810651