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Tools for working with the Earth Engine from a Jupyter development environment

Project description

earthengine-jupyter

NOTICE: This is an experimental project and is not an officially supported Google project. You are welcome to use it, but we do not guarantee stability.

How to use

This lib contains a Map class that can be used to display an interactive map.

import ee
from ee_jupyter.core import colab_gee_setup
from ee_jupyter.ipyleaflet import Map
colab_gee_setup()
Verifying environment is setup for earthengine-jupyter...
✓ The package earthengine-jupyter is already installed.
✓ Authentication credentials were found.
✓ Done.
# Intialize the Earth Engine client library.
ee.Initialize()
map1 = Map(center=(37.5924, -122.09), zoom=8)
map1
Map(center=[37.5924, -122.09], controls=(ZoomControl(options=['position', 'zoom_in_text', 'zoom_in_title', 'zo…

Define an Earth Engine image layer, and add it to the interactive map.

img1 = ee.Image("LANDSAT/LC09/C02/T1_L2/LC09_044034_20220127")
visualization = {
    'bands': ['SR_B4', 'SR_B3', 'SR_B2'],
    'min': 0.2 / 0.0000275,
    'max': 0.4 / 0.0000275,
}
map1.addLayer(eeObject=img1, visParams=visualization, name='Landsat scene')

We can also create an inspector object and associate it with the previously created map.

from ee_jupyter.ipyleaflet import Inspector

inspector1 = Inspector(map_object=map1)
inspector1
Inspector(layout=Layout(border_bottom='solid', border_left='solid', border_right='solid', border_top='solid', …

Typically when you create a inspector object, you will want to display it near the map.

from ipywidgets import HBox

display(HBox([map1, inspector1]))
HBox(children=(Map(center=[37.5924, -122.09], controls=(ZoomControl(options=['position', 'zoom_in_text', 'zoom…

Tip With Caption

Note that when viewed on GitHub Pages you can manipulate Jupyter widgets independently, but the widgets do not interact with each other. To experience the cross-widget interactivity, open up this notebook in a Jupyter environment.

Displaying a Map Image

If you want to display a static (non-interactive) image, you can do that as well. The embed=True parameter will allow the image to be saved within the notebook.

from IPython.display import Image


visualization['dimensions'] = 400  # maximum dimension for the image
url = img1.getThumbUrl(visualization)

Image(url=url, format='png', embed=True)

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