Jupyter

Here are some tools for working with Google Earth Engine from a Jupyter development environment which provide a foundation for new libraries on top of the Google Earth Engine Python API.

Here you can find introductions and Jupyter Notebook examples on how to access Radiant MLHub API.

European Centre for Medium-Range Weather Forecasts (ECMWF) has released more than 40 notebooks to help users reproduce their weather charts. Just click on any chart with a Project Jupyter icon.

Learn how to publish your Jupyter notebooks as web tools with this step-by-step example. This functionality is available from ArcGIS Enterprise version 10.9.1.

Here is a collection of Jupyter notebooks for learning Google Earth Engine Python API and geemap, assembled by geemap's author, Dr. Qiusheng Wu.

Here is a video recording of a 90-min workshop introducing leafmap, featuring Dr. Qiusheng Wu, Assistant Professor of Geography at the University of Tennessee, Knoxville.

The leafmap package is free and open-source, enabling users to analyze and visualize geospatial data with minimal coding in a Jupyter environment, such as Google Colab and Jupyter Notebook.

Ever wanted to view local raster files in a Jupyter notebook? Check out this local tile server to do just that.

The geemap package is built upon ipyleaflet and ipywidgets, and enables users to analyze and visualize Google Earth Engine datasets interactively within a Jupyter-based environment.