rgee
An R binding package for calling Google Earth Engine API from within R.
https://github.com/r-spatial/rgee
Category: Sustainable Development
Sub Category: Data Catalogs and Interfaces
Keywords
earth-engine earthengine google-earth-engine googleearthengine r spatial-analysis spatial-data
Keywords from Contributors
dataviz weather bird climate colab folium ipyleaflet ipywidgets qgis geospatial-data
Last synced: about 12 hours ago
JSON representation
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 5 years ago)
- Default Branch: master
- Last Pushed: 2025-04-21T18:28:50.000Z (5 days ago)
- Last Synced: 2025-04-21T19:36:54.771Z (5 days ago)
- Topics: earth-engine, earthengine, google-earth-engine, googleearthengine, r, spatial-analysis, spatial-data
- Language: R
- Homepage: https://r-spatial.github.io/rgee/
- Size: 31.7 MB
- Stars: 723
- Watchers: 38
- Forks: 152
- Open Issues: 58
- Releases: 15
-
Metadata Files:
- Readme: README.md
- Changelog: NEWS.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.md
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
README.md
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.
var db = 'CGIAR/SRTM90_V4'
var image = ee.Image(db)
print(image.bandNames())
#> 'elevation'
import ee
ee.Initialize(project = "my-project-id")
db = 'CGIAR/SRTM90_V4'
image = ee.Image(db)
image.bandNames().getInfo()
#> [u'elevation']
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 RETICULATE_PYTHON and EARTHENGINE_GCLOUD every time you authenticate/init your account.
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()
# 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:
install.packages("rgee")
Install the development versions from github with
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.
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 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)
rgee::ee_install()
- Use ee_install_set_pyenv (Recommended for users with experience in Python environments)
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:
rgee::ee_install_set_pyenv(
py_path = "/usr/bin/python3",
py_env = NULL
)
However, rgee::ee_install_upgrade 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.
ee_check() # Check non-R dependencies
Sync rgee with other Python packages
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
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
JS version)
1. Compute the trend of night-time lights (Authenticate and Initialize the Earth Engine R API.
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.
createTimeBand <-function(img) {
year <- ee$Date(img$get('system:time_start'))$get('year')$subtract(1991L)
ee$Image(year)$byte()$addBands(img)
}
Use your TimeBand function to map it over the night-time lights collection.
collection <- ee$
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.
col_reduce <- collection$reduce(ee$Reducer$linearFit())
col_reduce <- col_reduce$addBands(
col_reduce$select('scale'))
ee_print(col_reduce)
Let's visualize our map!
Map$setCenter(9.08203, 47.39835, 3)
Map$addLayer(
eeObject = col_reduce,
visParams = list(
bands = c("scale", "offset", "scale"),
min = 0,
max = c(0.18, 20, -0.18)
),
name = "stable lights trend"
)
2. Let's play with some precipitation values
Install and load tidyverse
and sf
R packages, and initialize the Earth Engine R API.
library(tidyverse)
library(rgee)
library(sf)
ee_Initialize(project = "my-project-id")
Read the nc
shapefile.
nc <- st_read(system.file("shape/nc.shp", package = "sf"), quiet = TRUE)
We will use the Terraclimate dataset to extract the monthly precipitation (Pr) from 2001
terraclimate <- ee$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$rename(sprintf("PP_%02d",1:12)) # rename the bands of an image
ee_extract
will help you to extract monthly precipitation values from the Terraclimate ImageCollection. ee_extract
works similar to raster::extract
, you just need to define: the ImageCollection object (x), the geometry (y), and a function to summarize the values (fun).
ee_nc_rain <- ee_extract(x = terraclimate, y = nc["NAME"], sf = FALSE)
Use ggplot2 to generate a beautiful static plot!
ee_nc_rain %>%
pivot_longer(-NAME, names_to = "month", values_to = "pr") %>%
mutate(month, month=gsub("PP_", "", month)) %>%
ggplot(aes(x = month, y = pr, group = NAME, color = pr)) +
geom_line(alpha = 0.4) +
xlab("Month") +
ylab("Precipitation (mm)") +
theme_minimal()
JS version)
3. Create an NDVI-animation (Install and load sf
. after that, initialize the Earth Engine R API.
library(magick)
library(rgee)
library(sf)
ee_Initialize(project = "my-project-id")
Define the regional bounds of animation frames and a mask to clip the NDVI data by.
mask <- system.file("shp/arequipa.shp", package = "rgee") %>%
st_read(quiet = TRUE) %>%
sf_as_ee()
region <- mask$geometry()$bounds()
Retrieve the MODIS Terra Vegetation Indices 16-Day Global 1km dataset as an ee.ImageCollection
and then, select the NDVI band.
col <- ee$ImageCollection('MODIS/006/MOD13A2')$select('NDVI')
Group images by composite date
col <- col$map(function(img) {
doy <- ee$Date(img$get('system:time_start'))$getRelative('day', 'year')
img$set('doy', doy)
})
distinctDOY <- col$filterDate('2013-01-01', '2014-01-01')
Now, let's define a filter that identifies which images from the complete collection match the DOY from the distinct DOY collection.
filter <- ee$Filter$equals(leftField = 'doy', rightField = 'doy')
Define a join and convert the resulting FeatureCollection to an ImageCollection... it will take you only 2 lines of code!
join <- ee$Join$saveAll('doy_matches')
joinCol <- ee$ImageCollection(join$apply(distinctDOY, col, filter))
Apply median reduction among the matching DOY collections.
comp <- joinCol$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.
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.
rgbVis <- comp$map(function(img) {
do.call(img$visualize, visParams) %>%
ee$Image$clip(mask)
})
Let's animate this. Define GIF visualization parameters.
gifParams <- list(
region = region,
dimensions = 600,
crs = 'EPSG:3857',
framesPerSecond = 10
)
Get month names
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.
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. 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.
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
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 🙌 👏 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:
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' - 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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: 2025-03-31T15:24:52.010Z
- Profile URL: https://github.com/r-spatial
GitHub Events
Total
- Issues event: 16
- Watch event: 40
- Issue comment event: 34
- Push event: 73
- Pull request review event: 4
- Pull request review comment event: 4
- Pull request event: 10
- Fork event: 7
- Create event: 1
Last Year
- Issues event: 16
- Watch event: 40
- Issue comment event: 34
- Push event: 73
- Pull request review event: 4
- Pull request review comment event: 4
- Pull request event: 10
- Fork event: 7
- Create event: 1
Committers metadata
Last synced: 7 days ago
Total Commits: 1,223
Total Committers: 22
Avg Commits per committer: 55.591
Development Distribution Score (DDS): 0.409
Commits in past year: 134
Committers in past year: 6
Avg Commits per committer in past year: 22.333
Development Distribution Score (DDS) in past year: 0.179
Name | Commits | |
---|---|---|
Cesar Luis Aybar Camacho | a****4@g****m | 723 |
GitHub Action | a****n@g****m | 393 |
Antony Barja | a****8@g****m | 27 |
Roy Yali Samaniego | r****3@g****m | 17 |
valeriallactayo | v****o@u****e | 14 |
gcarrascoe | g****1@g****m | 12 |
Jacob B. Socolar | j****r@g****m | 12 |
Matthieu Stigler | M****r@g****m | 9 |
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 |
egbendito | e****o@g****m | 1 |
Committer domains:
- zhaw.ch: 1
- maslab.aitech.ac.jp: 1
- tudelft.nl: 1
- unmsm.edu.pe: 1
- github.com: 1
Issue and Pull Request metadata
Last synced: 1 day ago
Total issues: 146
Total pull requests: 17
Average time to close issues: 3 months
Average time to close pull requests: about 1 month
Total issue authors: 100
Total pull request authors: 11
Average comments per issue: 3.19
Average comments per pull request: 0.94
Merged pull request: 13
Bot issues: 0
Bot pull requests: 0
Past year issues: 22
Past year pull requests: 7
Past year average time to close issues: 19 days
Past year average time to close pull requests: 22 days
Past year issue authors: 19
Past year pull request authors: 6
Past year average comments per issue: 1.91
Past year average comments per pull request: 0.86
Past year merged pull request: 6
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- TianyaImpression (8)
- MatthieuStigler (7)
- Leprechault (6)
- zackarno (6)
- wilson733 (4)
- fBedecarrats (4)
- agronomofiorentini (3)
- rokoeh (3)
- aloboa (2)
- POTCHARAARIYA (2)
- SvenVw (2)
- jimoreira (2)
- MelanieDickie (2)
- ambarja (2)
- Cidree (2)
Top Pull Request Authors
- valeriallactayo (4)
- MatthieuStigler (3)
- ambarja (2)
- fpirotti (1)
- bbest (1)
- jdbcode (1)
- NONONOexe (1)
- csaybar (1)
- pfrater (1)
- MarShaikh (1)
- bmaitner (1)
Top Issue Labels
- question (13)
- bug (12)
- priority (5)
- enhancement (3)
- good first issue (3)
- rgeeExtra feature (2)
- help wanted (2)
- documentation (1)
Top Pull Request Labels
Package metadata
- Total packages: 2
-
Total downloads:
- cran: 1,704 last-month
- 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
- Licenses: Apache License (≥ 2.0)
- Latest release: 1.1.7 (published over 1 year ago)
- Last Synced: 2025-04-25T14:04:54.683Z (1 day ago)
- Versions: 8
- Dependent Packages: 3
- Dependent Repositories: 13
- Downloads: 1,704 Last month
- Docker Downloads: 21,622
-
Rankings:
- Forks count: 0.416%
- Stargazers count: 0.628%
- Docker downloads count: 6.446%
- Average: 6.719%
- Dependent repos count: 8.065%
- Downloads: 11.463%
- Dependent packages count: 13.3%
- Maintainers (1)
conda-forge.org: r-rgee
- Homepage: https://github.com/r-spatial/rgee/, https://r-spatial.github.io/rgee/, https://github.com/google/earthengine-api/
- Licenses: Apache-2.0
- Latest release: 1.1.5 (published over 2 years ago)
- Last Synced: 2025-04-01T02:09:18.766Z (26 days ago)
- Versions: 5
- Dependent Packages: 0
- Dependent Repositories: 0
-
Rankings:
- Forks count: 14.46%
- Stargazers count: 16.177%
- Average: 28.959%
- Dependent repos count: 34.025%
- Dependent packages count: 51.175%
Dependencies
- actions/cache v1 composite
- actions/checkout v2 composite
- r-lib/actions/setup-pandoc master composite
- r-lib/actions/setup-r master composite
- actions/checkout v2 composite
- r-lib/actions/setup-r v2 composite
- r-lib/actions/setup-r-dependencies v2 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- ad-m/github-push-action v0.6.0 composite
- R >= 3.3.0 depends
- R6 * imports
- cli * imports
- crayon * imports
- jsonlite * imports
- leafem * imports
- leaflet >= 2.0.2 imports
- magrittr * imports
- methods * imports
- processx * imports
- reticulate >= 1.24 imports
- rstudioapi >= 0.7 imports
- covr * suggests
- digest * suggests
- future * suggests
- gargle * suggests
- geojsonio * suggests
- googleCloudStorageR >= 0.6.0 suggests
- googledrive >= 2.0.0 suggests
- httr * suggests
- knitr * suggests
- leaflet.extras2 * suggests
- magick * suggests
- png * suggests
- raster * suggests
- rgdal * suggests
- rmarkdown * suggests
- sf * suggests
- spelling * suggests
- stars * suggests
- testthat * suggests
Score: 19.80975571060304