Earth Observation Data Science Cookbook

This Project Pythia Cookbook covers a range of Earth observation examples employing the Pangeo philosophy. The examples represent the main research lines and BSc/MSc courses at the Department of Geodesy and Geoinformation at the TU Wien (Austria). The department has strong ties with the EODC (Earth Observation Data Centre For Water Resources Monitoring), which hosts e.g., analysis-ready Sentinel-1 (imaging radar mission) data, and has the computational resources to process large data volumes.

Motivation

The motivation behind this book is to provide examples of Pangeo-based workflows applied to realistic examples in Earth observation data science. Creating an effective learning environment for Earth observation students is a challenging task due to the rapidly growing volume of remotely sensed, climate, and other Earth observation data, along with the evolving demands from the tech industry. Today's Earth observation students are increasingly becoming a blend of traditional Earth system scientists and "big data scientists", with expertise spanning computer architectures, programming paradigms, statistics, and machine learning for predictive modeling. As a result, it is essential to equip educators with the proper tools for instruction, including training materials, access to data, and the necessary skills to support scalable and reproducible research.

Authors

Wolfgang Wagner, Martin Schobben, Nikolas Pikall, Joseph Wagner, Davide Festa, Felix David Reuß, Luka Jovic

Contributors

Structure

This book comprises examples of data science 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, 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:

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

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

1. Move into the eo-datascience-cookbook directory bash cd eo-datascience-cookbook
2. Create and activate your conda environment from the environment.yml file bash conda env create -f environment.yml conda activate eo-datascience-cookbook-dev
3. Move into the notebooks directory and start up Jupyterlab bash cd notebooks/ jupyter lab