Earth Observation Datascience Cookbook

This Project Pythia Cookbook covers a range of earth observation example employing the Pangeo philosophy.

Motivation

The motivation behind this book is to provide some examples of Pangeo-based workflows applied to realistic examples in earth observation.

Authors

Wolfgang Wagner, Martin Schobben, Nikolas Pikall

Contributors

Structure

This book comprises examples of datascience concerning Earth Observation (EO) data, including course material on remote sensing and data products produced by the TU Wien. It also serves to showcase the data and services offered by the EODC (Earth Observation Data Centre For Water Resources Monitoring Gmbh), including a STAC catalogue and a Dask Gateway for distributed data processing.

Courses

This section offers an overview of notebooks, which are used in courses from the Department of Geodesy and Geoinformation at TU Wien.

Templates

This section provides a collection of general examples of earth observation related tasks and workflows, which are not directly related to a specific course or product.

Tutorials

In this section you will find a collection of lessons, which explain certain products or methods that have been developed at the Department of Geodesy and Geoinformation at TU Wien.

Running the Notebooks

You can either run the notebook using Binder or on your local machine.

Running on Binder

The simplest way to interact with a Jupyter Notebook is through Binder, which enables the execution of a Jupyter Book in the cloud. The details of how this works are not important for now. All you need to know is how to launch a Pythia Cookbooks chapter via Binder. Simply navigate your mouse to the top right corner of the book chapter you are viewing and click on the rocket ship icon, (see figure below), and be sure to select “launch Binder”. After a moment you should be presented with a notebook that you can interact with. I.e. you’ll be able to execute and even change the example programs. You’ll see that the code cells have no output at first, until you execute them by pressing {kbd}Shift+{kbd}Enter. Complete details on how to interact with a live Jupyter notebook are described in Getting Started with Jupyter.

Running on Your Own Machine

If you are interested in running this material locally on your computer, you will need to follow this workflow:

(Replace "cookbook-example" with the title of your cookbooks)

1. Clone the https://github.com/TUW-GEO/eo-datascience-cookbook repository:

    git clone https://github.com/TUW-GEO/eo-datascience-cookbook

2. Move into the eo-datascience-cookbook directory

   cd eo-datascience-cookbook

3. Create and activate your conda environment from the environment.yml file

   conda env create -f environment.yml
   conda activate eo-datascience-cookbook

4. Move into the notebooks directory and start up Jupyterlab

   cd notebooks/
   jupyter lab