Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

https://github.com/r-earthengine/ee_extra

A ninja python package that unifies the Google Earth Engine ecosystem.
https://github.com/r-earthengine/ee_extra

dataviz earth-engine geographic-information-systems gis google-earth-engine javascript landsat modis python python3 r remote-sensing rstats satellite-imagery sentinel

Last synced: about 2 months ago
JSON representation

A ninja python package that unifies the Google Earth Engine ecosystem.

Lists

README 

        




  ee_extra





    A Python package that unifies the Google Earth Engine ecosystem.





  

    EarthEngine.jl |

     rgee  | 

     rgee+  | 

     eemont

  







    PyPI





    conda-forge





    License





    Documentation Status





    Tests





    Awesome Spectral Indices





    GEE STAC





    Scale and Offset





    ee-appshot





    Black





    isort






---



**GitHub**: [https://github.com/r-earthengine/ee_extra](https://github.com/r-earthengine/ee_extra)



**Documentation**: [https://ee-extra.readthedocs.io](https://ee-extra.readthedocs.io)



**PyPI**: [https://pypi.python.org/pypi/ee_extra](https://pypi.python.org/pypi/ee_extra)



**Conda-forge**: [https://anaconda.org/conda-forge/ee_extra](https://anaconda.org/conda-forge/ee_extra)



---



## Overview



[Google Earth Engine](https://earthengine.google.com/) (GEE) is a cloud-based service for 

geospatial processing of vector and raster data. The Earth Engine platform has a 

[JavaScript and a Python API](https://developers.google.com/earth-engine/guides) with 

different methods to process geospatial objects. Google Earth Engine also provides a 

[HUGE PETABYTE-SCALE CATALOG](https://developers.google.com/earth-engine/datasets/) of 

raster and vector data that users can process online. 



There are a lot of fantastic third-party GEE packages and projects around GitHub. However,

most of them are coded in JavaScript or Python, and they are not straightforward

to translate to R, Julia, or other programming languages. The main goal of `eeExtra` is

to guarantee a smooth `import` of these projects in other programming languages by

standardizing different methods and enabling the use of JavaScript modules outside the

[Code Editor](https://code.earthengine.google.com/).





  ee_extra_diagram




Some of the `eeExtra` features are listed here:



- Automatic scaling and offsetting.

- Spectral Indices computation (using [Awesome Spectral Indices](https://github.com/davemlz/awesome-spectral-indices)).

- Clouds and shadows masking.

- STAC related functions.



And the most important feature:



- Enabling the usage of JavaScript modules outside the Code Editor.



## How does it work?



`eeExtra` is a Python package, just like any other, but it is a *ninja* that serves as a 

methods provider for different environments: R, Julia and Python itself. `eeExtra` 

accomplish this by being the powerhouse of some amazing packages such as [rgee](https://github.com/r-spatial/rgee),

[rgee+](https://github.com/r-earthengine/rgeeExtra), and [eemont](https://github.com/davemlz/eemont).



Public JavaScript module can also be used outside the Code Editor in these packages

through `eeExtra`. For this, `eeExtra` implements a rigorous JavaScript translation

module that allows users to install, require and use JavaScript modules as if they

were on the Code Editor!



You may be wondering *"Why is it a ninja package?"*, well, that's a valid question,

the whole point of `eeExtra` resides in the fact that nobody has to use `eeExtra` itself,

but rather use one of the packages that are powered by `eeExtra`! :) 



## Installation



Install the latest version from PyPI:



```

pip install ee_extra

```



Install soft ee_extra dependencies:



```

pip install jsbeautifier regex

```



Upgrade `eeExtra` by running:



```

pip install -U ee_extra

```



Install the latest version from conda-forge:



```

conda install -c conda-forge ee_extra

```



Install the latest dev version from GitHub by running:



```

pip install git+https://github.com/r-earthengine/ee_extra

```



## Features



Let's see some of the awesome features of `eeExtra` and how to use them from the powered

packages in python and R!



### Scale and Offset



Most datasets in the data catalog are scaled and in order to get their real values,

we have to scale (and sometimes offset) them!



 Python (eemont) 

 R (rgee+) 

 Julia (EarthEngine.jl) 



  

``` python

import ee, eemont

ee.Initialize()

db = 'COPERNICUS/S2_SR'

S2 = ee.ImageCollection(db)

S2.scaleAndOffset()

```



``` r

library(rgee)

library(rgeeExtra)

ee_Initialize()

db <- 'COPERNICUS/S2_SR'

S2 <- ee$ImageCollection(db)

ee_extra_scaleAndOffset(S2)

```



``` julia

using PyCall

using EarthEngine



Initialize()



ee_extra = pyimport("ee_extra")

ee_core = ee_extra.STAC.core

db = "COPERNICUS/S2_SR"

S2 = ee.ImageCollection(db)

ee_core.scaleAndOffset(S2)

```



### Spectral Indices



Do you know the [Awesome Spectral Indices](https://github.com/davemlz/awesome-spectral-indices)? 

Well, you can compute them automatically with `eeExtra`! 



 Python (eemont) 

 R (rgee+) 

 Julia (EarthEngine.jl) 



  

``` python

import ee, eemont

ee.Initialize()

db = 'COPERNICUS/S2_SR'

S2 = ee.ImageCollection(db)

S2 = S2.scaleAndOffset()

S2.spectralIndices("EVI")

```



``` r

library(rgee)

library(rgeeExtra)

ee_Initialize()

db <- 'COPERNICUS/S2_SR'

S2 <- ee$ImageCollection(db)

S2 <- ee_extra_scaleAndOffset(S2)

ee_extra_spIndices(S2, "EVI")

```



  

```julia

using PyCall

using EarthEngine



Initialize()



ee_extra = pyimport("ee_extra")

ee_core = ee_extra.STAC.core

ee_sp = ee_extra.Spectral.core

db = "COPERNICUS/S2_SR"

S2 = ee.ImageCollection(db)

S2 = ee_core.scaleAndOffset(S2)

ee_sp.spectralIndices(S2, "EVI")

```

  

  



### STAC features



Access STAC properties easily!



 Python (eemont) 

 R (rgee+) 

 Julia (EarthEngine.jl) 



  

``` python

import ee, eemont

ee.Initialize()

db = 'COPERNICUS/S2_SR'

S2 = ee.ImageCollection(db)

S2.getSTAC()

```



``` r

library(rgee)

library(rgeeExtra)

ee_Initialize()

db <- 'COPERNICUS/S2_SR'

S2 <- ee$ImageCollection(db)

ee_extra_getSTAC()

```



  



``` julia

  

using PyCall

using EarthEngine



Initialize()



ee_extra = pyimport("ee_extra")

ee_core = ee_extra.STAC.core

db = "COPERNICUS/S2_SR"

S2 = ee.ImageCollection(db)

ee_core.getSTAC(S2)



```



  



### JavaScript Modules



This is perhaps the most important feature in `eeExtra`! What if you could use a

JavaScript module (originally just useful for the Code Editor) in python or R? Well,

wait no more for it!



  - **JS Code Editor**



``` javascript

var mod = require('users/sofiaermida/landsat_smw_lst:modules/Landsat_LST.js')



var geom = ee.Geometry.Rectangle(-8.91, 40.0, -8.3, 40.4)

var LST = mod.collection("L8", "2018-05-15", "2018-05-31", geom, true)



print(LST)

```



  - **Python eemont**  



``` python

import ee, eemont



ee.Initialize()

module = 'users/sofiaermida/landsat_smw_lst:modules/Landsat_LST.js'

ee.install(module)

mod = ee.require(module)



geom = ee.Geometry.Rectangle(-8.91, 40.0, -8.3, 40.4)

LST = mod.collection("L8", "2018-05-15", "2018-05-31", geom, True)

print(LST)

```



  - **R rgeeExtra**  



``` r

library(rgee)

library(rgeeExtra)



ee_Initialize()



lsmod <- 'users/sofiaermida/landsat_smw_lst:modules/Landsat_LST.js'

mod <- module(lsmod)



geom <- ee$Geometry$Rectangle(-8.91, 40.0, -8.3, 40.4)

LST <- mod$collection("L8", "2018-05-15", "2018-05-31", geom, TRUE)

print(LST)

```

  

  - **Julia EarthEngine.jl**



``` julia

using PyCall

using EarthEngine



Initialize()



ee_extra = pyimport("ee_extra")

landsat_module = "users/sofiaermida/landsat_smw_lst:modules/Landsat_LST.js"

ee_extra.install(landsat_module)

lsmodule = ee_extra.require(landsat_module)



geom = Rectangle(-8.91, 40.0, -8.3, 40.4)

LST = lsmodule.collection("L8", "2018-05-15", "2018-05-31", geom, true)

print(LST)

```