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Wageningen International Conference Centre

Summer School 2020

The OpenGeoHub Summer School 2020 will be held at the Wageningen Int. Conference Centre (Hotel and Conference centre). To receive updates please register for the R-sig-geo mailing list, OpenGeoHub Twitter channel, and/or subscribe for the OpenGeoHub newsletter. The Summer School is limited to 70 100 participants.

Working programme

For updates and questions please use the Mattermost channel.

Latest updates: Based on the Dutch Goverment new rules from 6th of May, we have a green light from WICC to do the Summer School. Participant will be obliged, however, to closely follow the new WICC rules, most importantly the 1.5m distance at any time.

In the case the event is cancelled for security reasons such as the Coronavirus outbreak or similar, all participants will be offered to participate in the postponed event or be refunded. The bank transfer costs, however, in all cases must be covered by the participants. Follow the status of the Coronavirus outbreak in the Netherlands here.

The OpenGeoHub 2020 Summer School aims at bringing together the leading FOSS4G and R spatial developers (i.e. actual people involved in developing, documenting and maintaining packages). Lecturers will run tutorials and introduction / motivation speeches which will be partially video-recorded. The topics of the summer school are:

  • New R packages and functionality, new FOSS4G software and standards,

  • Geocomputing using R and Open Source GIS GDAL, GRASS GIS, SAGA GIS, QGIS,

  • Processing large raster data sets using R,

  • Combining geocomputing using R and Python,

  • Using FOSS4G software for predictive soil, vegetation and environmental mapping,

The special theme of the Summer School 2020 is:

"Developing Machine Learning Algorithms for spatial and spatiotemporal data science problems"

Course fees:

The registrations fees for this Summer School full course fee are 550 EUR. Registration fees cover costs of using facilities, lunch and coffee breaks, administration costs, local travel costs, and costs of travel and accommodation for lecturers. Participants from ODA countries (employed by an organization or company in ODA-listed country) and/or full-time students (not under work contract as University assistant or similar) have a right on reduced fee (340 EUR).

Summer School is organized on a cost-recovery basis. OpenGeoHub foundation is a not-for-profit research foundation located in the Netherlands. All lecturers are volunteers. None of the lecturers receives any honorarium payment or is contracted by the local organizers.

Venue and accommodation:

We have pre-booked 70 rooms at the Wageningen Int. Conference Centre (WICC) for the duration of the Summer School with a special reduced rate for all participants. Please do not contact or book accommodation WICC independently as this might result in different room rates. Room sharing is possible (please specify during registrations) and can lead to further decrease in accommodation costs.

Wageningen ("City of Life Sciences") is a student town with a population of about 45,000 from which about 13,000 students. Wageningen University's researchers are active around the globe, and the university hosts students from over 100 countries.

Important dates:

  • 26th of November 2019 — registrations open,

  • 1st of February 2020 — registrations close,

  • 16th 28th of February 2020 — selection of candidates and invitation letters sent,

  • 12th of April 2020 — course fee payment deadline,

  • 14th of May 2020 — extended deadline for participants from the waiting list, 

  • 1st of June 2020 — official programme published,

  • 16 August to 22 August 2020 — Summer School,


Unsorted. The final programme will be based on the voting for topics during registrations.

avatar   Edzer Pebesma (Institute for Geoinformatics, University of Münster)
  • "Handling and analysing vector and raster data cubes with R"
avatar   Hanna Meyer (Institute of Landscape Ecology, University of Münster)
  • "Machine learning in remote sensing applications"
avatar   Meng Lu (Department of Physical Geography, Faculty of Geosciences, Utrecht University)
  • "Assessment of global air pollution exposure"
avatar   Paula Moraga (Department of Mathematical Sciences, University of Bath)
  • "Spatial modeling and interactive visualization with the R-INLA package"
avatar   Giuseppe Amatulli (Yale University / Spatial Ecology)
  • "GDAL/OGR and PKTOOLS for massive raster/vector operations"
avatar   Richard Barnes (University of California Berkeley)
  • "High-performance geocomputing for hydrological / terrain modeling"
  • "Leveraging Python, clusters, and GPUs for geocomputation"
  • "Reproducible scientific analysis"
avatar   Tim Appelhans (MeterGroup)
  • "mapview package tutorial"
avatar   Madlene Nussbaum (Bern University of Applied Sciences)
  • "Mastering machine learning for spatial prediction I — overview and introduction in methods"
  • "Mastering machine learning for spatial prediction II — model selection and interpretation, uncertainty"
avatar   Dainius Masiliunas (Laboratory of Geo-information Science and Remote Sensing, Wageningen University & Research)
  • "Global-scale land cover mapping using FOSS4G"
  • "OpenEO demo (R client)"
  • "Detection of breaks in time series using the 'bfast' package in R"
avatar   Christian Knoth (Institute for Geoinformatics, University of Münster)
  • "Introduction to Deep Learning in R for the analysis of UAV-based remote sensing data"
avatar   Marius Appel (Institute for Geoinformatics, University of Münster)
  • "Creating and Analyzing Multi-Variable Earth Observation Data Cubes in R"
avatar   Julia Wagemann (ECMWF / University of Marburg)
  • "Analysis of Big Earth Data with Jupyter Notebooks"
  • "Dashboarding with Jupyter Notebooks and Voila"
avatar   John E. Lewis (McGill University)
  • "Spatial mixed models & semiparametric regression"
  • "Working with and the modelling of temporal data"
  • "Using R for machine learning modelling — a coding introduction"
avatar   Longzhu Shen (Spatial Ecology)
  • "Predictive modeling of nitrogen distributions in US streams in a machine learning framework"
avatar   Tomislav Hengl (OpenGeoHub foundation)
  • "Automated predictive mapping using Ensemble Machine Learning"
  • "A step-by-step tutorial to optimization of geocomputing (tiling and parallelization) with R"
avatar   Leandro Parente (OpenGeoHub foundation)
  • "GEE toolbox: efficient computing using Google Earth Engine and R"

Other events of interest:

Video recordings:

Selection of lectures will be video recorded in high quality. Video recordings from the previous OpenGeoHub Summer Schools are available for viewing via our Youtube channel:

Playlist Summer School 2019