Advanced Spatial Analysis Workflows in R (ARGIPR)
Learn advanced spatial analysis workflows in R using sf & tmap. Practical online training in vector and spatial modelling workflows.
Duration: 6 Hours
Format: Recorded ‘on-demand’ Format
£250Registration Fee
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- Overview
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Course Description
This advanced two part course provides an in-depth exploration of advanced spatial analysis techniques using R, aimed at enhancing the ability to handle and interpret complex spatial data. Participants will gain practical skills in spatial statistics, spatial joins, buffering, point-in-polygon operations, and more, equipping them to conduct sophisticated spatial research effectively.
What You’ll Learn
- Hands-on practice with GeoDa and R for spatial data analysis
- Buffer creation and analysis in R
- Point-in-polygon operations for spatial decision making
- Intersect and intersection operations to understand spatial relationships
- Polygon-polygon overlays for complex spatial analysis
- Area-weighted spatial joins to integrate diverse data sources
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
Apply what you learn directly to your own data projects as you go, allowing for a personalized and immediately practical learning experience.
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 build on their existing spatial data and GIS knowledge or R scripting knowledge. It gives you the skills to answer questions using your data, and understand the advantages and limitations of this type of spatial data analysis. Participants can expect a highly interactive experience, with ample opportunity to engage with the material through practical exercises. Attendees will leave the workshop with not only theoretical knowledge but also practical skills applicable to their research. Spatial Statistics will be calculated using GeoDa (https://geodacenter.github.io/). 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.
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
Geographical Data and Spatial Statistics
Session 1 – 01:30:00 – Geographical Data and Spatial Statistics
- Spatial Autocorrelation Moran’s I
- Local Indicators of Spatial Association (LISA)
- Performing Analysis in GeoDa
- Performing Analysis in R
Session 2 – 01:30:00 – Spatial Joins and Buffer Creation
- Basic Spatial Joins
- Understanding Buffers
- Spatial Decision Making
Map Customisation and Automation in R
Session 3 – 01:30:00 – Point-in-Polygon Analysis
- Integrating Multiple Datasets
- Point-in-Polygon Techniques
Session 4 – 01:30:00 – Advanced Intersections and Overlays
- Polygon-Polygon Overlays
- Intersection Techniques
- Area-Weighted Spatial Joins
- Scenario Planning
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
Testimonials
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.
Carlos P.E. Bedson
Quantitative Spatial Ecology, Ecology and Environment Research Centre, Manchester Metropolitan University, United Kingdom
Courses attended
ADVR08, ENMR03, BMIN02, ISBD01, BADA01, SDMB06
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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