Introduction to Spatial Data analysis and GIS Workflows in R (IRGIPR)
Learn spatial data analysis and GIS workflows in R. Practical online training in sf, tmap, mapping, and spatial data processing.
Duration: 6 Hours
Format: Recorded ‘on-demand’ Format
£250Registration Fee
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- Overview
- Instructors
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Course Description
This 6-hpour course on spatial data analysis and GIS workflows in R provides a comprehensive introduction to using R as a GIS tool for spatial data analysis, focusing on importing, managing, processing, and visualizing spatial data. Participants will acquire essential skills to conduct sophisticated spatial analyses and produce complex maps, significantly enhancing their research projects. No previous experience of coding is required, although participants would benefit from some experience of using spatial data (e.g. Google Maps).
What You’ll Learn
- Importing Spatial Data: Handling spatial data including shapefiles and geopackages.
- Managing Spatial Data: Using spatial library `sf` to manage spatial data objects.
- Choropleth Maps: Creating choropleth maps to show data on a map.
- Visualizations: Enhancing map presentation with custom colour scales, legends, and thematic elements.
- Looping for Automation: Using loops in R to automate repetitive tasks and generate multiple maps efficiently.
- Real-world Examples: Applying learned techniques to real-world datasets.
- Interactive Maps: Introduction to creating interactive web maps using R.
- Using your own data: A chance to speak with Nick about finding and working with your own data.
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 ideal for anyone who wishes to use spatial data in their role, including researchers, students and anyone who has data with some spatial information (e.g. address, postcode, etc.) which they wish to show on a map. It is also suitable for those who wish to have an overview of what GIS and spatial data can be used for. The course covers some key theoretical concepts, with the bulk of the time spent on practical applications. All mapping and analysis will be performed using R, the free software environment for statistical computing and graphics (http://www.r-project.org/). Participants will learn to work with R packages sf and tmap. Instructors will provide datasets for the practical sessions, although participants are encouraged to bring their own data. This course requires no prior knowledge of GIS or coding. A level of basic computer experience is required.
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. A comprehensive list of required packages will also be shared with participants ahead of the course to allow for optional pre-installation.
Dr. Nick Bearman
Nick Bearman is a geospatial data scientist and GIS specialist with extensive experience in spatial analysis, data visualisation, and applied geospatial training. His work focuses on helping organisations and researchers make better decisions through the effective use of spatial data, combining technical expertise with a strong emphasis on communication and usability.
His core expertise includes Geographical Information Systems (GIS), spatial data visualisation, accessibility modelling, and the development of interactive mapping solutions. Nick has worked across a wide range of sectors, including public health, transport, retail, and environmental management, applying spatial analysis to real-world challenges.
Nick is the Director of Geospatial Training Solutions, where he delivers professional training in GIS, QGIS, and spatial data analysis. He is also actively involved in the wider geospatial community, contributing to training standards and supporting capacity building in open-source GIS.
Education & Career
- Director, Geospatial Training Solutions
· Certified QGIS Trainer (QGIS Certification Programme)
· Extensive experience delivering GIS and spatial data training internationally
· Background in geography and spatial data science
Research & Professional Focus
Nick’s work centres on applied spatial analysis and improving how organisations use geographic data. He specialises in translating complex spatial workflows into accessible, practical tools for decision-making, with particular strengths in accessibility modelling and geospatial visualisation.
Current Work
- Delivery of GIS and QGIS training courses for professional and academic audiences
· Development of spatial data workflows and mapping solutions
· Consultancy in accessibility analysis and geospatial decision support
Professional Consultancy
Nick works with public and private sector organisations to develop spatial data strategies, build analytical capacity, and implement GIS solutions. His consultancy spans transport planning, health accessibility, and location-based analysis.
Teaching & Skills
- Specialist in GIS, QGIS, and spatial data analysis
· Experienced trainer in applied geospatial workflows and visualisation
· Strong focus on reproducible analysis and effective communication of spatial data
· Advocate for open-source geospatial tools and best practices
Links
Session 1 – 01:30:00 – Introduction to R and Spatial Data Basics
- Setting up R and RStudio
- Working with spatial data formats
- Basic spatial data handling
- Introduction to ‘sf’ library
- Importing shapefiles
Session 2 – 01:30:00 – Classification and Creating a Choropleth Map
- Creating choropleth maps
- Classifying spatial data
- Different classification methods
Session 3 – 01:30:00 – Map Customisation and Automation in R
- Customizing map visuals
- Automating with loops
- Generating multiple maps efficiently
- Adding legends and thematic elements
Session 4 – 01:30:00 – Clustering of Crime Points and Working with your Own Data
- Working with point data
- Reprojecting data to different CRS
- Exporting data to shapefiles
- Interactive web maps with R
Testimonials
PR Stats 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 PR Stats 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
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PR Stats provided excellent training in stable isotope analysis through the SIMMPR course, which was incredibly valuable for my research. I was fortunate to attend the course through a generous fee waiver, which directly supported my work and enabled me to develop skills that contributed to my recent publication on reservoir food webs in Sri Lanka. I’m very grateful for the opportunity and support, and would highly recommend their courses to others working in ecological research.
Subodha Silva
Aquatic Ecology Researcher
Courses attended
SIMMPR
Testimonials
PR Stats has become an invaluable part of developing my skills in advanced statistical and spatial analysis. Through training in areas such as Bayesian statistics and Species Distribution Modelling, I’ve gained both practical expertise and exposure to leading experts in the field. The impact on my research has been significant with at least four of my published papers have been directly influenced by PR Stats courses. My most recent work benefitted from modelling advice on sample design and model accuracy evaluation and can be seen here.
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Courses attended
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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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