Spatial Data Visualisation and Mapping using TMAP
Visualize spatial data in R with tmap. Learn to create static and interactive maps using sf, terra, and stars in this 20-hour on-demand course.
Duration: 20 Hours
Format: Recorded ‘on-demand’ Format
£450Registration Fee
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- Overview
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Course Description
What You’ll Learn
During the course will cover the following:
- Know how to use the core packages sf, terra, and stars to read and process spatial data in R, including joining data sources and performing geospatial data manipulations.
- Understand the methodological advantages and limitations of different map types, enabling informed decisions based on data characteristics and target users.
- Create various types of thematic maps, including choropleths, bivariate maps, cartograms, glyph maps, and 3d maps.
- Learn how to select colours, taking several properties such as contrast and color blindness into account.
- Be able to fine-tune map layouts in tmap, including adding map components, customizing legends, and incorporating map insets.
- Be able to use tmap for exploring, analysing, and presenting spatial data.
- Know how to export maps in various static and interactive formats.
- Learn how to use tmap extension packages.
Course Format
Flexible Learning Structure
Learn through a carefully structured mix of lecture recordings and guided exercises that you can pause, revisit, and complete at your own pace—ideal for busy professionals or those balancing multiple commitments.
Access Anytime, Anywhere
All course content is available on-demand, making it accessible across all time zones without the need to attend live sessions or adjust your schedule.
Independent Exploration with Support
Engage deeply with course topics through self-directed study, with the option to reach out to instructors via email for clarification or deeper discussion.
Comprehensive Learning Resources
Gain full access to the same high-quality materials provided in live sessions, including code, datasets, and presentation slides—all available to download and keep. Please note recordings can only be streamed.
Work With Your Own Data, On Your Terms
Apply what you learn directly to your own data projects as you go, allowing for a personalized and immediately practical learning experience.
Continued Guidance and Resource Access
Receive 30 days of post-enrolment email support and unrestricted access to all session recordings during that time, so you can review and reinforce your learning as needed.
Who Should Attend / Intended Audiences
This course is intended for academics and postgraduate students working on spatial data projects, as well as applied researchers and analysts in the public, private, or third sectors who require the reproducibility, speed, and flexibility of a command-line language like R for spatial data analysis and visualisation. It is also well-suited for data journalists aiming to produce engaging and informative maps for news stories, dashboards, and infographics, and for current R users seeking to update their skills with spatial data packages, particularly tmap. Participants should have a basic understanding of mathematical and statistical concepts and be comfortable using R, including tasks such as importing and exporting data, manipulating data frames, and creating simple exploratory plots. Familiarity with tidyverse packages—especially dplyrand tidyr—is recommended, as is experience with git.
Equipment and Software requirements
A laptop or desktop computer with a functioning installation of R and RStudio is required. Both R and RStudio are free, open-source programs compatible with Windows, macOS, and Linux systems.
While not essential, using a large monitor—or ideally a dual-monitor setup—can significantly enhance your learning experience by allowing you to view course materials and work in R simultaneously.
All necessary R packages will be introduced and installed during the workshop.
Dr. Martijn Tennekes
Martijn is a statistician and data scientist with two decades of experience in teaching, academic research, and applied consulting. He specialises in data visualisation, spatial data analysis, and statistical programming, with a strong focus on open-source tools and reproducible research. An R enthusiast, Martijn is the main author of several widely used R packages for data analysis and mapping.
His career spans collaborations with numerous academic institutions, including Eindhoven University of Technology and the University of Oxford, and he has led multiple training courses for the European Commission (Eurostat). Martijn is currently based at Statistics Netherlands, where he works in the methodology department contributing to international research and innovation in statistical methods.
Martijn holds a PhD in game theory from Maastricht University (2010) and has since applied his theoretical background to practical challenges in data science and spatial analytics.
Education & Career
• 20 years of experience in statistical consulting, academic research, and teaching
• PhD in Game Theory, Maastricht University (2010)
• Senior Methodologist at Statistics Netherlands
• Course leader for Eurostat (European Union) training programs
• Collaborator with universities (including Eindhoven and Oxford) and intergovernmental organisations.
Research Focus
Martijn’s work focuses on the development and application of statistical programming techniques for data visualisation and spatial data analysis. He is particularly interested in leveraging R for creating reproducible, insightful data products and visual tools that support decision-making in research and policy.
Current Projects
• Development of R packages for spatial and statistical visualisation
• Applied research in statistical methodology at Statistics Netherlands
• Training on statistical computing and spatial data analysis with R across Europe
Teaching & Skills
• Expert in R programming, spatial analysis, and statistical visualisation
• Experienced in teaching R for applied data science, mapping, and modelling
• Active contributor to the R community and open-source development
Links
• GitHub
• TMAP
• LinkedIn
• ResearchGate
Session 1 – 01:00:00 – Overview of the core R packages for spatial data analysis and visualisation.
Session 2 – 01:00:00 – Creating Common Thematic Map Types Using the R Package tmap
Session 3 – 01:00:00 – Exploring Colour Palettes with the R Package cols4all
Session 4 – 01:00:00 – Methodology of Spatial Data Visualisation
Session 5 – 01:00:00 – Review of exercises
Session 6 – 01:00:00 – Introduction to Map Projections (Coordinate Reference Systems)
Session 7 – 01:00:00 – Working with Vector Data in R Using the sf Package
Session 8 – 01:00:00 – Visualisation of Vector Data with tmap
Session 9 – 01:00:00 – Review of exercises
Session 10 – 01:00:00 – Creating Cartograms with the R package tmap.cartogram
Session 11 – 01:00:00 – Using Basemaps in tmap
Session 12 – 01:00:00 – Working with Raster Data in R Using the terra package
Session 13 – 01:00:00 – Review of exercises
Session 14 – 01:00:00 – Working with Spatiotemporal Data Cubes in R using the stars Package
Session 15 – 01:00:00 – Visualisation of Raster Data with tmap
Session 16 – 01:00:00 – Exporting Static and Interactive Maps
Session 17 – 01:00:00 – Review of exercises
Session 18 – 01:00:00 – Integrating tmap with the R Package Shiny for Dashboards
Session 19 – 01:00:00 – Fine-tuning Map Layouts for High-quality Publications
Session 20 – 01:00:00 – Extension packages of tmap: tmap.cartogram, tmap.networks, tmap.glyphs, and tmap.mapgl
Testimonials
PRStats offers a great lineup of courses on statistical and analytical methods that are super relevant for ecologists and biologists. My lab and I have taken several of their courses—like Bayesian mixing models, time series analysis, and machine/deep learning—and we've found them very informative and directly useful for our work. I often recommend PRStats to my students and colleagues as a great way to brush up on or learn new R-based statistical skills.
Rolando O. Santos
PhD Assistant Professor, Florida International University
Courses attended
SIMM05, IMDL03, ITSA02, GEEE01 and MOVE07
Testimonials
PRStats offers a great lineup of courses on statistical and analytical methods that are super relevant for ecologists and biologists. My lab and I have taken several of their courses—like Bayesian mixing models, time series analysis, and machine/deep learning—and we've found them very informative and directly useful for our work. I often recommend PRStats to my students and colleagues as a great way to brush up on or learn new R-based statistical skills.
Rolando O. Santos
PhD Assistant Professor, Florida International University
Courses attended
SIMM05, IMDL03, ITSA02, GEEE01 and MOVE07
Testimonials
PRStats offers a great lineup of courses on statistical and analytical methods that are super relevant for ecologists and biologists. My lab and I have taken several of their courses—like Bayesian mixing models, time series analysis, and machine/deep learning—and we've found them very informative and directly useful for our work. I often recommend PRStats to my students and colleagues as a great way to brush up on or learn new R-based statistical skills.
Rolando O. Santos
PhD Assistant Professor, Florida International University
Courses attended
SIMM05, IMDL03, ITSA02, GEEE01 and MOVE07
Frequently asked questions
Everything you need to know about the product and billing.
When will I receive instructions on how to join?
You’ll receive an email on the Friday before the course begins, with full instructions on how to join via Zoom. Please ensure you have Zoom installed in advance.
Do I need administrator rights on my computer?
I’m attending the course live — will I also get access to the session recordings?
I can’t attend every live session — can I join some sessions live and catch up on others later?
I’m in a different time zone and plan to follow the course via recordings. When will these be available?
I can’t attend live — how can I ask questions?
Will I receive a certificate?
When will I receive instructions on how to join?
You’ll receive an email on the Friday before the course begins, with full instructions on how to join via Zoom. Please ensure you have Zoom installed in advance.
Do I need administrator rights on my computer?
I’m attending the course live — will I also get access to the session recordings?
I can’t attend every live session — can I join some sessions live and catch up on others later?
I’m in a different time zone and plan to follow the course via recordings. When will these be available?
I can’t attend live — how can I ask questions?
Will I receive a certificate?
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