Adapting to the Recent Changes in R Spatial Packages (sf, terra, PROJ library)
Update Your R Spatial Skills: From sp/raster to sf/terra/PROJ7
Duration: 15 Hours
Format: Recorded ‘on-demand’ Format
£350Registration Fee
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- Overview
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Course Description
R statistical software is becoming increasingly popular for spatial analysis and mapping. This is partially due to a large number of R packages devoted to applying various spatial methods. These packages, however, are being revised, updated, or even superseded to allow for better performance, simpler user interface, or expanded capabilities. Substantial recent changes in R spatial packages include developing the ‘sf’ package as a successor of ‘sp’, creation of `terra` as a successor of `raster`, and establishing the `stars` package. Additionally, all of these packages were affected by the recent major updates of the PROJ library. In this course, we will learn to use key packages for the analysis of spatial data, both vector (‘sf’) and raster (‘terra’), and see how they differ from their older counterparts, ‘sp’ and ‘raster’. Another important aspect of the course will be to understood spatial projections and coordinate systems, how the recent PROJ changes affect R users, and how to adjust to them.
What You’ll Learn
During the course we will cover the following:
- The basic concepts behind spatial analysis ecosystem in R.
- How packages such as sp/rgeos/rgdal/raster differ from their successor’s sf/terra/star.
- Switching from using packages such as sp/rgeos/rgdal/raster to sf/terra/stars.
- Basic concepts behind spatial projections, and how PROJ.7 differs from PROJ4.
- How to deal with coordinate reference systems in R.
- Have the confidence to switch from PROJ4 to PROJ7 (i.e., for instance, adjusting old scripts based on PROJ4)?.
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 designed for academics, post-graduate students, and applied researchers working with spatial data, as well as current R users wanting to update their knowledge (e.g. moving from sp to sf or from raster to terra). It is suitable for intermediate R users interested in modern spatial tools, and for beginners with prior experience in geographic data or GIS software. While understanding basic GIS concepts such as spatial vectors, rasters, and coordinate reference systems is helpful but not essential, attendees should be comfortable with R basics such as reading CSV files, creating simple plots, and manipulating data frames. Experience with packages like sp or raster is an advantage, but those with strong GIS knowledge and some programming experience may also find the course appropriate.
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.
Jakub Nowosad
Jakub is a computational geographer whose work lies at the intersection of geocomputation, environmental science, and spatial data analysis. His research focuses on developing and applying spatial methods to improve understanding of environmental processes and patterns. A vital part of his work is creating, collaborating on, and improving geocomputational software, with a strong emphasis on reproducibility and accessibility.
He is an active member of the #rspatial community and co-author of the widely used books Geocomputation with R and Geocomputation with Python, which have become key resources for researchers and practitioners in spatial analysis. His contributions span methodological development, software implementation, and applied research in environmental and ecological sciences.
Education & Career
• PhD in Geography, Adam Mickiewicz University, Poland
• Associate Professor, Institute of Geoecology and Geoinformation, Adam Mickiewicz University, Poland
Research Focus
Jakub’s work centres on:
• Development and application of spatial methods for environmental and ecological data
• Geocomputation and the creation of reproducible, open-source spatial workflows
• Integration of spatial statistics, machine learning, and data science for environmental monitoring and modelling
• Improving accessibility and usability of geospatial software tools for research and teaching
Current Projects
• Developing open-source R packages for spatial data analysis and environmental modelling (e.g., spDataLarge, motif, and spatialexplain)
• Advancing reproducible methods for large-scale ecological and environmental datasets
• Co-authoring educational resources and materials to support geocomputation using programming languages
• Collaborating on interdisciplinary projects in ecology, geography, and data science
Professional Consultancy & Teaching
Jakub provides expert training in spatial data science and geocomputation for academic, professional, and applied research projects. He teaches a wide range of topics including:
• Geocomputation with R
• Spatial statistics and modelling
• Environmental applications of spatial analysis
• Reproducible research workflows in R and open-source tools
He also actively contributes to open-source communities and advocates for open, transparent, and collaborative science.
Links
• Website/Blog
• GitHub
• ResearchGate
• ORCID
• Mastodon
Session 1 – 04:00:00 – Overview of spatial analysis ecosystem in R
Available R packages for spatial analysis in R, How do R packages represent spatial objects, and how are they connected with each other, Importance of using the more recent R spatial packages, such as ‘sf’ or ‘terra’, Main concepts behind map projections (geoids, datums, geographic/projected coordinates, types of projections, etc.), Implementation of these concepts in the PROJ library (used by most R spatial packages), Differences between PROJ.4 and its newer versions (e.g. PROJ.7)
Session 2 – 04:00:00 – Spatial vector data analysis in R
Spatial vector data processing & analysis in R, Read/write/and visualize spatial vector data, Differences between ‘sp’/’rgdal’/’rgeos’ and ‘sf’, Moving from ‘sp’ to ‘sf’ for spatial vector data processing & analysis, Spherical geometry: how this concept was recently implemented in sf, and what is an impact of this implementation
Session 3 – 04:00:00 – Spatial raster data analysis in R
Spatial raster data processing & analysis in R, Read/write/and visualize spatial raster data, Differences between ‘raster’ and ‘stars’/’terra’, Moving from ‘raster’ to ‘terra’ for spatial raster data processing & analysis, Short overview of package ‘stars’
Session 4 – 03:00:00 – Coordinate reference systems
How to switch from PROJ.4 to PROJ.7 in R.
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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