earthengine-jupyter

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earthengine-jupyter

(★ 82)

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

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- - deploy.yaml
  - test.yaml
- code-of-conduct.md
- contributing.md
- __init__.py
- _modidx.py
- colab.py
- core.py
- ipyleaflet.py
- layout.py
- - cell-10-output-1.png
- 00_colab.ipynb
- 00_core.ipynb
- 01_ipyleaflet.ipynb
- 02_layout.ipynb
- _quarto.yml
- index.ipynb
- nbdev.yml
- sidebar.yml
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CHANGELOG.md
custom.yml
LICENSE
MANIFEST.in
nbdev.yml
README.md
settings.ini
setup.py
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// repository documentation

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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.**

## Setup

``` python
try:
  import ee_jupyter
  print('ee_jupyter was already installed.')
except ModuleNotFoundError:
  print('ee_jupyter was not found. Installing now...')
  import os
  result = os.system('pip -q install earthengine-jupyter')
```

## How to use

This lib contains a
[`Map`](https://google.github.io/earthengine-jupyter/ipyleaflet.html#map)
class that can be used to display an interactive map.

``` python
import ee
from ee_jupyter.core import authenticate_if_needed
from ee_jupyter.ipyleaflet import Map
from ee_jupyter.layout import MapWithInspector
import ipywidgets as widgets
```

``` python
authenticate_if_needed()
```

``` python
# Intialize the Earth Engine client library.
ee.Initialize()
```

``` python
map1 = Map(center=(37.5924, -122.09), zoom=8)
map1
```

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

``` python
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.

``` python
from ee_jupyter.ipyleaflet import Inspector

inspector1 = Inspector(map_object=map1)
inspector1
```

Typically when you create a inspector object, you will want to display
it with the map. The `MapWithInpsector` object adds a button that
toggles the inspector functionality.

The map below shows a Sentinel-2 image covering Paris. Click on the
inspector toggle button to open the inspector.

``` python
map_init_paris = {'center':(49.4, 2.3), 'zoom':8}
m = MapWithInspector(**map_init_paris)
image = ee.Image('COPERNICUS/S2_SR_HARMONIZED/20220604T104619_20220604T104620_T31UDQ')
m.map.addLayer(image, {'bands': ['B4', 'B3', 'B2'], 'max': 2500}, 'Landsat image')
m
```

<div>

> **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.

</div>

# 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.

``` python
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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