Advanced Static Cartography in R (ASCR01)
Turn spatial data into clear, publication-quality maps using advanced cartography in R.
Duration: 3 Days, 5 hours per day
Next Date: June 3-5, 2026
Format: Live Online Format
UK (GMT+1) local time - All sessions will be recorded and made available to ensure accessibility for attendees across different time zones.
£350Registration Fee
Register NowLike what you see? Click and share!
5.0
from 200+ reviews
- Overview
- Instructors
- Schedule
Course Description
R has become a powerful environment not only for spatial analysis but also for producing high-quality maps. While many introductory courses focus on basic choropleths and simple map layouts, advanced cartography requires more sophisticated techniques to effectively communicate complex spatial patterns.
This course focuses on advanced static cartographic techniques in R, using the tmap package as the central mapping framework. You will learn how to design expressive and publication-quality thematic maps by combining tmap with specialized extensions and supporting packages.
Throughout the course we explore advanced visualization techniques such as bivariate choropleths, glyph maps, grid maps, cartograms, and network maps. Special attention is given to cartographic design principles, including the selection of effective and color-blind friendly color palettes, choosing appropriate basemaps, and designing insets such as inset maps, inset charts, and fully customized inset elements.
By the end of the course, you will be able to design clear, visually compelling, publication-quality maps that communicate complex spatial information effectively.
What You’ll Learn
During the course you will learn:
- How to use tmap as a flexible framework for advanced static cartography in R
- How to create bivariate choropleth maps using bivariate color palettes (with cols4all)
- How to design effective multivariate maps with clear visual hierarchies
- How to create glyph maps such as donut maps and flower maps using tmap.glyphs
- How to design grid maps using geofacet and gridmappr in combination with tmap
- How to create cartograms (Dorling, contiguous, and non-contiguous) using tmap.cartogram
- How to visualize spatial networks using tmap.networks together with sfnetworks
- How to design insets, including inset maps, inset charts, and custom inset elements
- How to select effective color palettes, including color-blind friendly palettes and palettes with strong visual contrast
- How to choose and evaluate basemaps, including when basemaps are useful and when they should be avoided
- How to design clear and effective publication-quality thematic maps
Course Format
Interactive Learning Format
Each day features a well-balanced combination of lectures and hands-on practical exercises, with dedicated time for discussing participants’ own data, time permitting.
Global Accessibility
All live sessions are recorded and made available on the same day, ensuring accessibility for participants across different time zones.
Collaborative Discussions
Open discussion sessions provide an opportunity for participants to explore specific research questions and engage with instructors and peers.
Comprehensive Course Materials
All code, datasets, and presentation slides used during the course will be shared with participants by the instructor.
Personalized Data Engagement
Participants are encouraged to bring their own data for discussion and practical application during the course.
Post-Course Support
Participants will receive continued support via email for 30 days following the course, along with on-demand access to session recordings for the same period.
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 need to produce high-quality, publication-ready maps using R. It is also well suited for data journalists and analysts who want to communicate complex spatial patterns through clear and compelling thematic maps.
Because this is an advanced cartography course, participants are expected to already have experience working with R. You should be comfortable performing common tasks such as importing and exporting data, manipulating data frames, and producing basic visualizations.
Experience with spatial data packages such as sf, terra, or stars is recommended, as these will be used throughout the course for handling vector and raster data.
Prior experience with tmap is a bonus, but not strictly required. Participants who have previously created basic maps with tmap will benefit most from the advanced cartographic techniques covered in this course.
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.
A working webcam is recommended to support interactive elements of the course. We encourage participants to keep their cameras on during live Zoom sessions to foster a more engaging and collaborative environment.
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. A comprehensive list of required packages will also be shared with participants ahead of the course to allow for optional pre-installation.
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 9 – 01:00:00 – Introduction and overview of advanced cartography in R
Session 10 – 01:00:00 – Designing effective thematic maps in tmap
Break – 01:00:00
Session 11 – 01:00:00 – Color palette selection (color-blind friendly palettes, contrast, palette design)
Session 12 – 01:00:00 – Bivariate choropleths and multivariate thematic mapping
Session 5 – 01:00:00 – Review of exercises and discussion
Session 6 – 01:00:00 – Glyph maps: donut maps and flower maps using tmap.glyphs
Break – 01:00:00
Session 7 – 01:00:00 – Grid maps using geofacet and gridmappr
Session 8 – 01:00:00 – Cartograms: Dorling, contiguous, and non-contiguous
Session 9 – 01:00:00 – Review of exercises and discussion
Session 10 – 01:00:00 – Insets: inset maps, inset charts, and custom inset elements
Break – 01:00:00
Session 11 – 01:00:00 – Network visualization using sfnetworks and tmap.networks
Session 12 – 01:00:00 – Basemap selection and final map design
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?
Still have questions?
Can’t find the answer you’re looking for? Please chat to our friendly team.
