Visualizing Spatial Ecological Data
Master ecological spatial visualisation using R: remote sensing, species distributions, color-safe maps, and more.
Duration: 40 hours
Format: Recorded ‘on-demand’ Format
£480Registration Fee
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Course Description
This intensive, five-day course introduces participants to techniques in spatial data visualization, with a strong focus on ecological applications. Designed for researchers, data analysts, and environmental scientists, the course blends theory with hands-on practice using R.
Participants will explore spatial matrices and remote sensing data, learn to visualize spatial and temporal variability, simulate species distributions, and address common challenges in ecological data visualization, including accessibility issues like colorblindness. Tools and techniques covered include RGB plotting, raster matrix analysis, cartograms, spatial density mapping, and best practices for color-safe graph design.
attendees will be equipped with a robust toolkit for interpreting spatial patterns in ecological systems and communicating them effectively through clear, reproducible visualizations.
What You’ll Learn
During the course will cover the following:
- Visualizing ecosystems using remote sensing data and RGB raster plotting.
- Measuring and interpreting spatial variability: distance- vs. abundance-based methods.
- Performing multivariate analysis and creating ridgeline plots for temporal patterns.
- Building scatterplots and using hexagon binning for dense spatial data.
- Analysing species distributions through cartograms, bivariate maps, and overlap metrics.
- Mapping spatial density and exploring point patterns using R.
- Creating accessible, colorblind-friendly scientific graphics using the tidyverse.
This course is designed for researchers and practitioners working with spatial and ecological data who seek to deepen their skills in spatial data visualization.
- Ecologists and environmental scientists aiming to interpret spatial patterns in ecosystems.
- Researchers and graduate students in ecology, geography, or related fields who work with remote sensing or species distribution data.
- Conservation practitioners and policy analysts who need to communicate complex spatial insights effectively.
- Educators and academic professionals developing teaching materials on ecological modeling or spatial analysis.
No prior knowledge of R is required. The course includes guided instruction and hands-on practice to help participants of all levels engage confidently with R-based tools and workflows.
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 researchers and practitioners working with spatial and ecological data who want to enhance their skills in spatial data visualization. It is particularly beneficial for ecologists and environmental scientists interpreting spatial patterns in ecosystems, researchers and graduate students in ecology, geography, or related fields using remote sensing or species distribution data, conservation practitioners and policy analysts communicating complex spatial insights, and educators developing materials on ecological modeling or spatial analysis. No prior experience with R or GitHub is required, as the course offers guided instruction and hands-on practice with beginner-friendly, step-by-step support. Participants will learn to use R for spatial data analysis and GitHub for version control, gaining the confidence and skills to apply these tools effectively in their research or professional work.
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.
Prof. Duccio Rocchini
Duccio is a spatial ecologist and remote sensing specialist whose work focuses on the integration of computational methods and open-source tools to measure and monitor biodiversity. His research explores the theoretical and applied dimensions of spatial ecology, with a strong emphasis on using satellite data, spectral diversity metrics, and landscape models to understand biodiversity patterns across scales.
Duccio’s career spans international collaborations with institutions such as the U.S. Geological Survey, the University of Nottingham (UK), the Ashoka Trust for Research in Ecology and the Environment (India), and UCLA. His early work in remote sensing and biodiversity laid the foundation for his continued focus on reproducible, open-source approaches in ecology.
Since 2019, Duccio has been Full Professor at the Alma Mater Studiorum – University of Bologna. Prior to this, he served as Associate Professor at the University of Trento and as a researcher at Fondazione Edmund Mach, where he was part of the GRASS GIS and Remote Sensing Group. He is a prominent advocate for open algorithms in spatial ecology and actively contributes to methodological advances in ecological modelling.
Education & Career
• PhD in Ecology with a focus on remote sensing and biodiversity (2005)
• Full Professor, University of Bologna (since 2019)
• Associate Professor, University of Trento (2017–2019)
• Researcher at Fondazione Edmund Mach, Trento (2009–2017)
• Collaborator with international institutions including USGS, UCLA, and ATREE (India)
Research Focus
Duccio’s research investigates how remotely sensed data and spatial models can quantify biodiversity and ecological change. He specialises in spectral diversity, spatial scaling, landscape metrics, and the development of open-source tools to support ecological theory and conservation applications.
Current Projects
• Development of spectral diversity indices for biodiversity monitoring
• Open-source algorithm design for spatial and theoretical ecology
• Cross-institutional research on scaling laws and landscape complexity in biodiversity science
Professional Consultancy
Duccio advises research groups and institutions on remote sensing applications, biodiversity modelling, and open-source GIS implementation. He is also active in promoting open science and reproducible research within the ecological community.
Teaching & Skills
• Expert in remote sensing, GIS, spatial modelling, and spectral diversity
• Experienced educator in ecology, spatial analysis, and biodiversity assessment
• Advocate for open-source tools and reproducible computational ecology
Links
• ResearchGate
Session 1 – 03:00:00 – Visualizing ecosystems through remote sensing data: RGB plotting and proper use of ggplot2 with raster matrices.
Session 2 – 03:00:00 – Spatial variability: Distance-based vs. abundance-based measures.
Session 3 – 02:00:00 – Multivariate analysis of ecological data
Session 4 – 02:00:00 – Temporal variability: Creating ridgeline plots
Session 5 – 02:00:00 – Scatterplots of remote sensing data and hexagon binning
Session 6 – 02:00:00 – Species distributions (Cartograms, overlap, and bivariate maps, Spatial density maps in R, Scatterplot matrices).
Session 7- 02:00:00 – Simulating spatial distributions of species in data cubes using the gcube package
Session 8 – 02:00:00 – Modeling virtual species
Session 9 – 03:00:00 – Challenges of colorblindness in scientific graphs
Session 10 – 03:00:00 – Designing colorblind-friendly visualizations for spatial data
Session 11 – 06:00:00 – Using LaTeX to produce output documentation
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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