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 70 120 participants. In the case of higher number of applications, candidates will be selected based on a ranking system, which is based on: time of registration, solidarity, academic output and contributions to the open source projects. To remove geographical bias, participants coming from more distant areas will have a priority on the rankings list.

Registrations are now closed. We have received a total of 203 applications. Due to high demand, we have decided to increase the maximum number of participants to 120. Rankings have been sent on 28/02/2020 and the invitation letters have been sent on 07/03/2020. If you are listed in the top 120 and have not received an email, please contact us a.s.a.p.  

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,

• 1st of May 2020 — official programme published,

• 16 August to 22 August 2020 — Summer School,

Lecturers:

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

		Edzer Pebesma (Institute for Geoinformatics, University of Münster)
Topics:		"Handling and analysing vector and raster data cubes with R"

		Hanna Meyer (Institute of Landscape Ecology, University of Münster)
Topics:		"Machine learning in remote sensing applications"

		Meng Lu (Department of Physical Geography, Faculty of Geosciences, Utrecht University)
Topics:		"Assessment of global air pollution exposure"

		Paula Moraga (Department of Mathematical Sciences, University of Bath)
Topics:		"Spatial modeling and interactive visualization with the R-INLA package"

		Giuseppe Amatulli (Yale University / Spatial Ecology)
Topics:		"GDAL/OGR and PKTOOLS for massive raster/vector operations"

		Richard Barnes (University of California Berkeley)
Topics:		"High-performance geocomputing for hydrological / terrain modeling" "Leveraging Python, clusters, and GPUs for geocomputation" "Reproducible scientific analysis"

		Tim Appelhans (MeterGroup)
Topics:		"mapview package tutorial"

		Madlene Nussbaum (Bern University of Applied Sciences)
Topics:		"Mastering machine learning for spatial prediction I — overview and introduction in methods" "Mastering machine learning for spatial prediction II — model selection and interpretation, uncertainty"

		Dainius Masiliunas (Laboratory of Geo-information Science and Remote Sensing, Wageningen University & Research)
Topics:		"Global-scale land cover mapping using FOSS4G" "OpenEO demo (R client)" "Detection of breaks in time series using the 'bfast' package in R"

		Christian Knoth (Institute for Geoinformatics, University of Münster)
Topics:		"Introduction to Deep Learning in R for the analysis of UAV-based remote sensing data"

		Marius Appel (Institute for Geoinformatics, University of Münster)
Topics:		"Creating and Analyzing Multi-Variable Earth Observation Data Cubes in R"

		Julia Wagemann (ECMWF / University of Marburg)
Topics:		"Analysis of Big Earth Data with Jupyter Notebooks" "Dashboarding with Jupyter Notebooks and Voila"

		John E. Lewis (McGill University)
Topics:		"Spatial mixed models & semiparametric regression" "Working with and the modelling of temporal data" "Using R for machine learning modelling — a coding introduction"

		Dylan Beaudette (National Soil Survey Center, USDA-NRCS)
Topics:		"Algorithms for Quantitative Pedology: R packages for working with soils data at scale" "High performance vector data analysis delivery with PostGIS" "Credible metrics for determining similarity, accuracy, and precision in the context of soil type mapping"

		Longzhu Shen (Spatial Ecology)
Topics:		"Predictive modeling of nitrogen distributions in US streams in a machine learning framework"

		Tomislav Hengl (OpenGeoHub foundation)
Topics:		"Automated predictive mapping using Ensemble Machine Learning" "A step-by-step tutorial to optimization of geocomputing (tiling and parallelization) with R"

Other events of interest:

• 27–30 May 2020, eRUM, Milan, Italy,

• 1–5 June 2020, Geocomputation Using Free & Open Source Software, Matera, Italy,

• 7–10 July 2020, UseR 2020, St. Louis USA,

• 27–31 July 2020, GeoPython 2020,

• 20–24 August 2020, FOSS4G 2020 Calgary Canada,

• 20–24 August 2020, EurSoil, Geneve CH,

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: