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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.
https://github.com/projectpythia/eo-datascience-cookbook

Category: Sustainable Development
Sub Category: Education

Keywords

earth-observation remote-sensing

Last synced: about 13 hours ago
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Earth Observation Data Science Cookbook provides training material centered around Earth Observation data while honoring the Pangeo Philosophy. The examples used in the notebooks represent some of the main research lines of the Remote Sensing Unit at the Department of Geodesy and Geoinformation at the TU Wien (Austria).

README.md

Earth Observation Data Science Cookbook

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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:

     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

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this cookbook, please cite it as below."
authors:
  # add additional entries for each author -- see https://github.com/citation-file-format/citation-file-format/blob/main/schema-guide.md
  - family-names: Wagner
    given-names: Wolfgang
    orcid: https://orcid.org/0000-0001-7704-6857
    website: https://www.tuwien.at/mg/dekanat/mitarbeiter-innen
    affiliation: Technische Universität Wien, Vienna, Austria, EODC Earth Observation Data Centre for Water Resources Monitoring, Austria
  - family-names: Schobben
    given-names: Martin
    orcid: https://orcid.org/0000-0001-8560-0037
    website: https://github.com/martinschobben
    affiliation: Technische Universität Wien, Vienna, Austria
  - family-names: Pikall
    given-names: Nikolas
    website: https://github.com/npikall
    affiliation: Technische Universität Wien, Vienna, Austria
  - family-names: Wagner
    given-names: Joseph
    affiliation: Technische Universität Wien, Vienna, Austria
  - family-names: Festa
    given-names: Davide
    affiliation: Technische Universität Wien, Vienna, Austria
  - family-names: Reuß
    given-names: Felix David
    affiliation: Technische Universität Wien, Vienna, Austria
  - family-names: Jovic
    given-names: Luka
    affiliation: Technische Universität Wien, Vienna, Austria
  - name: "Earth Observation Data Science contributors" # use the 'name' field to acknowledge organizations
    website: "https://github.com/TUW-GEO/eo-datascience-cookbook/graphs/contributors"
title: "Earth Observation Data Science Cookbook"
abstract: "Earth Observation Data Science Cookbook provides training material \
  centered around Earth Observation data while honoring the Pangeo Philosophy. \
  The examples used in the notebooks represent some of the main research lines \
  of the Remote Sensing Unit at the Department of Geodesy and Geoinformation \
  at the TU Wien (Austria). In addition, the content familiarizes the reader \
  with the data available at the EODC (Earth Observation Data Centre For Water \
  Resources Monitoring) as well as the computational resources to process
  large amounts of data."

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Last synced: 3 months ago

Total issues: 4
Total pull requests: 11
Average time to close issues: about 1 month
Average time to close pull requests: 19 days
Total issue authors: 3
Total pull request authors: 6
Average comments per issue: 3.0
Average comments per pull request: 1.09
Merged pull request: 8
Bot issues: 0
Bot pull requests: 5

Past year issues: 4
Past year pull requests: 11
Past year average time to close issues: about 1 month
Past year average time to close pull requests: 19 days
Past year issue authors: 3
Past year pull request authors: 6
Past year average comments per issue: 3.0
Past year average comments per pull request: 1.09
Past year merged pull request: 8
Past year bot issues: 0
Past year bot pull requests: 5

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/projectpythia/eo-datascience-cookbook

Top Issue Authors

  • MartinSchobben (2)
  • erogluorhan (1)
  • npikall (1)

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  • dependabot[bot] (5)
  • ktyle (2)
  • erogluorhan (1)
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Dependencies

.github/workflows/nightly-build.yaml actions
.github/workflows/publish-book.yaml actions
.github/workflows/trigger-book-build.yaml actions
.github/workflows/trigger-delete-preview.yaml actions
.github/workflows/trigger-link-check.yaml actions
.github/workflows/trigger-preview.yaml actions
.github/workflows/trigger-replace-links.yaml actions
  • actions/checkout v4 composite
  • jacobtomlinson/gha-find-replace v3 composite
  • stefanzweifel/git-auto-commit-action v5 composite
environment.yml conda
  • jupyter-book
  • jupyterlab
  • sphinx-pythia-theme

Score: -Infinity