earthengine-py-notebooks

A collection of 360+ Jupyter Python notebook examples for using Google Earth Engine with interactive mapping

Contact: Qiusheng Wu (https://wetlands.io)

1. Description

This repository is a collection of 360+ Jupyter Python notebook examples. I developed these examples by converting my other repo qgis-earthengine-examples from Python scripts to Jupyter notebooks. Now you can display Earth Engine data layers interactively in Jupyter notebooks without having to install QGIS. Several Python packages are being used in these examples, including the Earth Engine Python API, folium, ipyleaflet, and geemap. The geemap Python package is built upon the folium and ipyleaflet packages and implements several methods for interacting with Earth Engine data layers, such as Map.addLayer(), Map.setCenter(), Map.centerObject(), and Map.setOptions().

2. Usage

• Step 1: Explore this repository and open any available Jupyter notebook in your browser (e.g., template.ipynb)
• Step 2: When the selected Jupyter notebook is open, click the Notebook Viewer link to view the interactive map.
• Step 3: If you would like to execute cells in the notebook interactively, you will need to Sign up for a Google Earth Engine account. Then you can click either Run in Google Colab to execute code interactively. This will allow you to add your own Earth Engine Python script.

3. How to automatically convert Earth Engine JavaScripts to Python scripts?

The following examples require the geemap package, which can be installed using pip install geemap. Check the Installation section for more information.

Launch an interactive notebook with Google Colab. Keep in mind that the conversion might not always work perfectly. Additional manual changes might still be needed. ui and chart are not supported. The source code for this automated conversion module can be found at conversion.py.

import os
from geemap.conversion import *

# Create a temporary working directory
work_dir = os.path.join(os.path.expanduser('~'), 'geemap')
# Get Earth Engine JavaScript examples. There are five examples in the geemap package folder. 
# Change js_dir to your own folder containing your Earth Engine JavaScripts, such as js_dir = '/path/to/your/js/folder'
js_dir = get_js_examples(out_dir=work_dir) 

# Convert all Earth Engine JavaScripts in a folder recursively to Python scripts.
js_to_python_dir(in_dir=js_dir, out_dir=js_dir, use_qgis=True)
print("Python scripts saved at: {}".format(js_dir))

# Convert all Earth Engine Python scripts in a folder recursively to Jupyter notebooks.
nb_template = get_nb_template()  # Get the notebook template from the package folder.
py_to_ipynb_dir(js_dir, nb_template)

# Execute all Jupyter notebooks in a folder recursively and save the output cells.
execute_notebook_dir(in_dir=js_dir)

4. Demo

5. Examples

The Table of Contents below mimics the structure of the Google Earth Engine API Documentation. I strongly encourage you to check out the API Documentation if you need an in-depth explanation of each Python example. Please note that the list below does not include all the Python examples contained in this repository. You are welcome to explore the repository and find more examples to suit your needs.

Get Started

• Hello world!
• Adding data to Map
• Finding images
• Band math
• Mapping (what to do instead of a for-loop)
• Reducing
• Image statistics
• Masking
• A complete example

Machine Learning

• Supervised Classification Algorithms
  • Classification and Regression Trees (CART) | Support Vector Machine (SVM) | Confusion Matrix
• Unsupervised Classification Algorithms
  • KMeans Clustering

Image

• Image Overview
• Image Visualization
• Image information and metadata
• Mathematical operations
• Relational, conditional and Boolean operations
• Convolutions
• Morphological Operations
• Gradients
• Edge detection
• Spectral transformations
• Texture
• Object-based methods
• Cumulative Cost Mapping
• Registering Images
• Miscellaneous
  • Band statistics (min, max, mean, std) | Image statistics by band | | | | | | | | | | | | | | | | | |

ImageCollection

• ImageCollection Overview
• ImageCollection Information and Metadata
• Filtering an ImageCollection
• [Mapping over an ImageCollection](https://github.com/giswqs/earthengine-py-notebooks/blob/mast