Geocomputation course

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Geocomputation using free and open source software

Monday 8 - Friday 12 July 2019


This postgraduate course provides participants with the opportunity to develop key skills required for advanced spatial data processing. Throughout the training, participants will focus on developing independent learning skills which will be fundamental for a continuous learning process of advanced data processing. This is a progressing journey of development with the availability of more complex data and the ongoing technological revolution. Within the course many different, complementary and sometimes overlapping tools will be presented to provide an overview of the existing open source software available for spatial data processing. We will discuss their strengths, weaknesses and specificity for different data processing objectives (e.g., modelling, data filtering, query, GIS analyses, graphics or reporting) and data types. In particular, we will guide participants to practice the use of different types of software and tools with the objective to assist in gaining a steep learning curve, which is generally experienced while using the new approach of analysing data within a programming command line environment. Broadly, we focus our training on helping participants to develop independent learning skills to find online help, solutions and strategies to fix bugs and independently progress with complex data processing problems.

The course programme is divided into the following areas of study and interactions:
Lectures: (15min to 1h each) Participants will take part in a series of lectures introducing basics functions of tools, theoretical aspects and background information, which is needed for a better understanding of the deeper concepts to be successively applied in data processing.
Hands on Tutorials: Participants will be guided during hands on sessions where trainers will perform data analyses on real case study datasets, while the participants fill follow those example procedure using their laptops. During tutorials sessions participants are supported by two trainers, one for the demonstrations and one to supervise the participants' work as well as helping with individual guidance on coding.
Hands on Exercises: In addition to tutorials and lectures, participants are encouraged to take up their own independent study during the exercise sessions. Specific tasks will be set allowing to reinforce the newly learned data processing capacity presented in lectures and practically learned during the tutorial sessions. Such exercise sessions equip participants with the confidence and skills to become independent learners and effectively engaged with the demands of advanced spatial-data processing.
Round table discussions: these sessions are mainly focused on exchanging experiences, needs and point of views. We aim at clarify specific participants' needs and challenges, focus on how to help and how to find solutions while problem solving.
Depending on the number of participants and their previous knowledge in programming, the more or the less topics can be addressed in accordance to the participants' needs. The exercises and examples will be cross-disciplinary: forestry, landscape planning, predictive modelling and species distribution, mapping, nature conservation, computational social science and other spatially related fields of studies. Nevertheless these case studies are template procedures and could be applied to any thematic applications and disciplines.

Learning outcomes

The course will enable participants to further develop and enhance their spatio-temporal data processing skills. Most importantly it will allow them to start using professionally a fully functional open source operating system including all required software toolkits. With continuous practice during the week participants will get familiar with a command line approach and focus on developing specific areas, including:

  • Developing a broad knowledge of existing tools and be able to judge the most appropriate one for their needs and which have more potential for their future learning.
  • Building confidence with the use of several command line utilities for spatial data processing and with Linux operating system.
  • Developing data processing skills and knowing more on data type, data modelling and data processing techniques.
  • Encouraging independent learning, critical thinking and effective data processing.
  • Day 1: Knowing each other / OSGeo-live operating system. Linux bash programming; AWK basic; Gnuplot plotting
  • Day 2: Gdal/OGR, Pktools, Orfeo Toolbox - Bash terminal; work with your data
  • Day 3: Grass - Bash terminal; work with your data
  • Day 4: Gdal and Geopandas - Python terminal; work with your data
  • Day 5: Machine Learning for geographical data - Python terminal; work with your data
General information
Target Group The course is aimed at PhD candidates, postdocs, and other academics that have a specific interest in geographical data analyses and a desire to leanr command line tools to process data.
Group Size Min. 15 / Max. 26 participants
Course duration 5 days
Language of instruction English
Frequency of recurrence Not yet determined. For now, one time only.
Number of credits 1.5 ECTS
Lecturers Dr. Giuseppe Amatulli (Research Scientist in GeoComputation and Spatial Science, Yale University, USA) and Dr. Longzhu Shen (University of Cambridge, UK)
Prior knowledge Participants should have basic computer skills and a strong desire to learn command line tools to process data. Prior experience in the use of Geographic Information Systems will be helpful.
Location Wageningen University Campus
Options for accommodation Accommodation is not included in the fee of the course, but there are several possibilities in Wageningen. For information on B&B's and hotels in Wageningen please visit Another option is Short Stay Wageningen. Furthermore Airbnb offers several rooms in the area. Finally, there are a number of groups on Facebook where students announce subrent possibilities and things like that. Examples include: Wageningen Room SubrentWageningen Room SubletsRoom Rent Wageningen, and Wageningen Student Plaza. Note that besides the restaurants in Wageningen, there are also options to have dinner on Wageningen Campus.
Fees 1
PE&RC / WIMEK PhD candidates with an approved TSP € 240,- € 290,-
a) All other PhD candidates
b) Postdocs and staff of the above mentioned Graduate Schools
€ 520,- € 570,-
All others € 760,- € 810,-

1 The course fee includes a reader, coffee/tea, and lunches. It does not include accommodation (NB: options for accommodation are given above)
2 The Early-Bird Fee applies to anyone who REGISTERS ON OR BEFORE 10 JUNE 2019


  • If you need an invoice to complete your payment, please send an email to, including ALL relevant details that should be mentioned on the invoice (e.g., purchase order no., specific addresses, attendees, etc.).
  • The Early-Bird policy is such that the moment of REGISTRATION (and not payment) is leading for determining the fee that applies to you.
  • Please make sure that your payment is arranged within two weeks after your registration.
  • It is the participant's responsibility to make sure that he/she (or his/her secretary) completes the payment correctly and in time.
PE&RC Cancellation Conditions
  • Up to 4 (four) weeks prior to the start of the course, cancellation is free of charge.
  • Up to 2 (two) weeks prior to the start of the course, a fee of € 240,- will be charged.
  • In case of cancellation within two weeks prior to the start of the course, a fee of € 520,- will be charged.
  • If you do not show at all, a fee of € 760,- will nevertheless be charged.

Note: If you would like to cancel your registration, ALWAYS inform us and do not assume that by NOT paying the participation fee, your registration is automatically cancelled, because it isn't (and do note that you will be kept to the cancellation conditions).

More information

Dr. Lennart Suselbeek (PE&RC)
Phone: +31 (0) 317 485426


To register, please enter your details below and click "Register".