A Python package that unifies the Google Earth Engine ecosystem.

EarthEngine.jl | rgee | rgee+ | eemont

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

Documentation: https://ee-extra.readthedocs.io

PyPI: https://pypi.python.org/pypi/ee_extra

Conda-forge: https://anaconda.org/conda-forge/ee_extra

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Overview

Google Earth Engine (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 with different methods to process geospatial objects. Google Earth Engine also provides a HUGE PETABYTE-SCALE CATALOG 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.

Some of the eeExtra features are listed here:

• Automatic scaling and offsetting.
• Spectral Indices computation (using 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, rgee+, and 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)
import ee, eemont ee.Initialize() db = 'COPERNICUS/S2_SR' S2 = ee.ImageCollection(db) S2.scaleAndOffset()	library(rgee) library(rgeeExtra) ee_Initialize() db <- 'COPERNICUS/S2_SR' S2 <- ee$ImageCollection(db) ee_extra_scaleAndOffset(S2)	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? Well, you can compute them automatically with eeExtra!

Python (eemont)	R (rgee+)	Julia (EarthEngine.jl)
import ee, eemont ee.Initialize() db = 'COPERNICUS/S2_SR' S2 = ee.ImageCollection(db) S2 = S2.scaleAndOffset() S2.spectralIndices("EVI")	library(rgee) library(rgeeExtra) ee_Initialize() db <- 'COPERNICUS/S2_SR' S2 <- ee$ImageCollection(db) S2 <- ee_extra_scaleAndOffset(S2) ee_extra_spIndices(S2, "EVI")	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)
import ee, eemont ee.Initialize() db = 'COPERNICUS/S2_SR' S2 = ee.ImageCollection(db) S2.getSTAC()	library(rgee) library(rgeeExtra) ee_Initialize() db <- 'COPERNICUS/S2_SR' S2 <- ee$ImageCollection(db) ee_extra_getSTAC()	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

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

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

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

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)