A Python package that unifies the Google Earth Engine ecosystem.
EarthEngine.jl |
rgee |
rgee+ |
eemont
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
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$ImageCollection(db)
ee_extra_getSTAC()
|
using PyCall
using EarthEngine
Initialize()
ee_extra = pyimport("ee_extra")
ee_core = ee_extra.STAC.core
db = "COPERNICUS/S2_SR"
S2 = ee.ImageCollection(db)
ee_core.getSTAC(S2)
|
JavaScript Modules
This is perhaps the most important feature in eeExtra
! What if you could use a
JavaScript module (originally just useful for the Code Editor) in python or R? Well,
wait no more for it!
var mod = require('users/sofiaermida/landsat_smw_lst:modules/Landsat_LST.js')
var geom = ee.Geometry.Rectangle(-8.91, 40.0, -8.3, 40.4)
var LST = mod.collection("L8", "2018-05-15", "2018-05-31", geom, true)
print(LST)
import ee, eemont
ee.Initialize()
module = 'users/sofiaermida/landsat_smw_lst:modules/Landsat_LST.js'
ee.install(module)
mod = ee.require(module)
geom = ee.Geometry.Rectangle(-8.91, 40.0, -8.3, 40.4)
LST = mod.collection("L8", "2018-05-15", "2018-05-31", geom, True)
print(LST)
library(rgee)
library(rgeeExtra)
ee_Initialize()
lsmod <- 'users/sofiaermida/landsat_smw_lst:modules/Landsat_LST.js'
mod <- module(lsmod)
geom <- ee$Geometry$Rectangle(-8.91, 40.0, -8.3, 40.4)
LST <- mod$collection("L8", "2018-05-15", "2018-05-31", geom, TRUE)
print(LST)
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)