OpenGeoHub Summer School Siegburg 2022 Begins

The summer school on earth systems data has kicked-started and is in full swing.

The OpenGeoHub Summer School 2022 (29th Aug-4 Sep) has many geospatial tutorials. This Summer School is a not-for-profit event and can be followed online.

The Summer School lectures will be live-streamed for free on (please note that it will not be possible to interact with lecturers)

Here is all the information that you need to know about this summer school including many other reasons why this will be beneficial and why you need to become part of it too.

Summer School 2022 / KISTE project workshop:
“Open Source solutions for Earth system data
(R, OSGeo, Python)”

Dates: 28 August 2022 – 03 September 2022 

Location: Friendly City Hotel Oktopus, Siegburg (Germany)

OpenGeoHub Summer School is an annual event that has been running at various locations in Europe and Canada and Australia since 2010. Every year, they invite researchers and specialists who they think are especially active (and successful) in developing open source software and open data, and helping other researchers improve their analysis and modeling frameworks. The 2022 event will be held in a hybrid form with physical lectures and hackathons with the support from the KISTE project. The Summer School will include:

  • Live presentations and demos by leading R and OSGeo developers,
  • 5 days of Earth System Analysis training sessions and R / OSGeo tutorials
    • Including 1 day of R-Spatial workshops,
    • Including 1 focus day “extreme events”
  • Discussion panels and break-out rooms.

This Summer School is a not-for-profit event and can be followed online.

Previous edition

OpenGeoHub Summer School 2020 in Wageningen (NL). Watch the full playlist.

  • A pan EU compilation of training points
    with GPS locations of trees and species name
  • Automated predictive mapping using
    Ensemble Machine Learning
  • Coding Machine Learning Models with R
    – Meet Tidymodels
  • Creating and Analyzing Multi-Variable Earth
    Observation Data Cubes in R (part 1)
  • Creating and Analyzing Multi-Variable Earth
    Observation Data Cubes in R (Part 2)

Livestream on YouTube:

The Summer School lectures will be live-streamed for free on OpenGeoHub YouTube channel.  (please note that it will not be possible to interact with lecturers)

Follow us

Discussion forum “Open Source software and data formats for Big EO data: how to choose between R, Python and/or Julia and different data formats?”

Register and follow the live stream on Eventbrite.
This event is open to everyone.

Register for free

Topics of interest

Topics of interested are focused around but not limited to (unsorted):

  • AI for Earth System Sciences 
  • Modelling Extreme Events (with ML/AI and statistics) (~1 day)
  • Classifying remote sensing time series data,
  • Design-based methods for assessing map accuracy,
  • Point pattern analysis in R,
  • Analysing spatiotemporal disease/health data,
  • Reproducible research,
  • Machine Learning and deep learning methods for spatial data,
  • Analyzing massive amounts of EO data in the cloud with R, gdalcubes, and STAC,
  • Running a Research Data infrastructure with OS Tools
  • WebGIS,
  • Geocomputation and spatial segmentation in R,
  • Static and interactive visualization of spatial data


Topics: “Machine learning for weather, air quality and climate”Martin SchultzForschungszentrum Jülich GmbH Institute for Advanced Simulation (IAS) Jülich Supercomputing Centre (JSC) [KISTE-Projekt]

Topics: “Explainable ML”Ribana RoscherRemote Sensing Group Institute of Geodesy and Geoinformation (IGG), University of Bonn [KISTE-Projekt]

Topics: “Open Reproducible Research (R tutorial)”Markus Konkol52°North

Topics: “Spatial modeling using mlr3” (R tutorial)Patrick Schratzmlr-org core team at cynkra

Topics: “Stochastic processes, analysis, examples” (Python tutorial)Markus AbelAmbrosys GmbH [KISTE-Projekt]

Topics: “Geocomputation with R’s guide to reproducible spatial data analysis” (R tutorial)Jakub NowosadAssistant Professor, Adam Mickiewicz University

Topics: “Accessing and using data cubes: spatial overlay, visualization and modeling” (R and Python tutorial)Leandro ParentePost-doctoral researcher, OpenGeoHub

Topics: “JuliaGeo: a gentle introduction”Martijn Visser & Maarten PronkHydrologist & Geodata scientist at Deltares

Topics: “R-spatial updates: sf, sftime, stars” (R tutorial)Edzer PebesmaProfessor IfGI, University of Muenste

Topics: “Visualization cloud-optimized (large) datasets in R” (R tutorial)Tim AppelhansDirector of Data Science – Meter Group

Topics: “GeoNode as Research Data Infrastructure”Christian AutermannResearch Software Engineer, 52°North Spatial Information Research GmbH

Topics: “Geo-pandas”Martin FleischmannResearch Associate in the Geographic Data Science Lab at the University of Liverpool

Topics: “Cross-language benchmarking: R, and Python”Krzystof DybaAdam Mickiewicz University

Topics: “Performance assessment and the area of applicability of spatial prediction models”Hanna MeyerProfessor, University of Muenster




Materials in terms of R-markdown tutorials, screen-recordings and similar will be provided to all participants before the start of the Summer School via our official Mattermost channel.

Social events & hackathon


Research Speed Dating

Recipe: Pre-order the group by their broader interest into subgroups. Split each subgroup equally where one half will be stationary and the other half be moving “clockwise” through the room. Pairs of people sit down for a given amount of time (~7 mins) and present their research topic to each other.

Science slam


Recipe: Interested participants sign up for a 3-min-madness where they pitch their research in 3 min “on stage” in front of all participants. Elect a jury (among the lecturers) that will ask quick questions and will finally vote for the “best pitch”. This could also be flavored towards a “science slam”. 


Reproducibility Hackathon

Participants can nominate their latest research for a reproducibility check. Share your paper and the associated resources with the group and let’s explore how far we can reproduce your study and whether everyone achieves the same result.

Why should you attend this event?

  1. Find out what are the trends in spatial analysis and modeling from the leading open source developers.
  2. Follow online demo’s / tutorials, ask questions, share your experiences and help us resolve important issues.
  3. Connect to similar participants and network. Find co-authors and co-creators that match your style of work and ambitions.
  4. Contribute to the Open Source community and global good.

Target communities

  • Open source development communities on github and gitlab,
  • R-sig-geo mailing list,
  • package users,
  • OSGeo community,
  • PhD and MSc level students in the field of environmental sciences, GIS, civil engineering, spatial modelling, GeoAI, Earth Sciences and similar,


We have made a reservation at the Friendly City Hotel Siegburg close to Bonn for the period 28.08.2022 – 03.09.2022. They offer large and well equipped conference rooms and the venue would also allow for us to host parallel sessions as in previous years.

The offer includes:

  • Air-conditioned conference room (max capacity 80 people) with balcony & including standard equipment (beamer, screen, 3 flipcharts, 3 moderator boards, paper & pencils);
  • Free internet access throughout Hotel (600Mbit);
  • Coffee & tea all day long from the specialty (in front of the conference room); soft drinks will be charged to according consumption;
  • Candy bar with sweet and sour delicacies (in front of the conference room);
  • Active break in the morning: coffee from the machine specialty & various tea, fruit juices & sandwiches;
  • Vital lunch at noon the finger food in front of the room or buffet in the restaurant included octopus water on the table;
  • Active break in the afternoon: coffee from the specialty machine & various tea, fresh-cut fruit and pastries;

Accommodation costs (fixed price):

  • 105 EUR bed & breakfast (single);
  • 140 EUR bed & breakfast (double occupancy);

The pricing is at the upper boundary of what appears reasonable. Rooms and facilities appear to be modern and of good quality. The hotel is rated 3-star and has a 8.1 on

Technology in use

  • Zoom Webinar livestreaming with Q&A box;
  • Mattermost channels for internal questions, screen sharing and markdown / code snippets;
  • Computational notebooks on and;

Virtual machines / software installation

For consistency we recommend that all participants use a prepared virtual machine (docker containers), best via:

  • Linux users: DistroBox;
  • Windows user: VirtualBox / alternative: WSL;

This would make sure that everyone follows exactly the same settings / same package versions etc.

Use of virtual containers / virtual OS comes at the cost of RAM, so we need to provide to all participants instructions on how to prepare and emphasize that their laptops should have a minimum configuration of 16GB RAM and similar.

Video recordings

All lectures will be video-recorded using Zoom webinar functionality in HD quality. Subject to approval of the presenters, the videos will be uploaded to and a DOI will be assigned to each talk. Lecturers will be asked to accept the general recording conditions and sign a document allowing for videos to be shared. Copyright of the video’s will be assigned to authors / presenters as in standard Open Access materials.

Code of conduct

Please read the Summer School Code of Conduct carefully before participating.

For more information about this programme, please visit or contact the information on this page.

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About the Author


Kumbirai is a freelance GIS Analyst and GIS Developer with innovative skills and interests in spatial epidemiology, Web-based GIS applications for sustainability, Space technology, Exploration, and Inclusive and Digital Land Information Systems all towards the attainment and achievement of the Global Sustainable Development Goals (SDGs) by 2030.

He is also a true believer of the power of location and geospatial intelligence to CHANGE THE WORLD in making it better for us ALL.

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