Learn how to turn complex geodata into clear insights using R. This hands-on course from Geo-ICT teaches you the skills to analyze, manage, and visualize spatial data using R Spatial—so you can tackle real-world challenges with confidence.
Learn how to turn complex geodata into clear insights using R. This hands-on course from Geo-ICT teaches you the skills to analyze, manage, and visualize spatial data using R Spatial—so you can tackle real-world challenges with confidence.
Geospatial data is everywhere—from the maps on your phone to the models used by governments and researchers to plan cities, manage resources, or respond to natural disasters. The ability to understand and analyze this kind of data is becoming increasingly valuable. That’s where R comes in.
R is one of the most powerful tools in data science and statistics, and with the right packages, it becomes a flexible and efficient platform for working with geospatial data. R Spatial is a suite of tools within the R ecosystem that allows you to perform advanced spatial analysis, create rich visualizations, and even build custom workflows to handle large datasets. With R Spatial, you’re not just plotting locations—you’re answering spatial questions, identifying trends, and supporting decisions with data.
It’s also a great tool for collaboration. R works smoothly with platforms like QGIS, making it easier to share data, generate visual output, and move between software environments. Whether you’re working in urban planning, climate research, environmental monitoring, or logistics, spatial analysis with R gives you a way to make sense of location-based information—and tell meaningful stories with your data.
At Geo-ICT, we’ve designed this course to give you the skills and confidence to work with geospatial data using R. Whether you’re new to R or want to strengthen your existing skills, this course is a solid step toward becoming a more capable, data-driven problem solver.
This course focuses on helping you develop a clear understanding of how to work with spatial data in R—from managing datasets to performing advanced analyses. You’ll begin by learning how to import geospatial files, manage different formats, and clean your data for analysis. You’ll also explore how to handle coordinate systems and work with attribute data linked to spatial features.
As you build your skills, you’ll dive into spatial operations like buffering, overlays, spatial joins, and aggregations. You’ll also learn to create effective visualizations—everything from simple maps to dynamic graphics that help communicate insights clearly. Along the way, you’ll explore tools and packages that make R Spatial so powerful, including how to automate tasks and improve your workflow.
We’ll also show you how to integrate R with QGIS, a popular open-source GIS platform. This combination opens up more possibilities for data exchange, presentation, and analysis, especially if you’re working with complex projects or collaborating with others.
Throughout the course, you’ll gain hands-on experience working with real datasets and step-by-step projects. The goal is simple: give you the skills you need to solve real geospatial problems using R—and do it with confidence.
We know there are plenty of options when it comes to learning GIS and data analysis. Here’s why Geo-ICT’s R Spatial course stands out:
Do you have questions about the course content? Not sure if the course aligns with your learning objectives? Or would you prefer a private session or in-company training? We’re happy to assist—feel free to get in touch.
R Spatial refers to the use of the R programming language for handling, analyzing, and visualizing spatial (geographic) data. Learning it gives you powerful open-source tools to perform GIS tasks, statistical modeling, and create high-quality maps.
This course is ideal for students, researchers, and professionals in fields such as geography, environmental science, urban planning, and data science who want to integrate spatial analysis into their workflows.
You’ll learn how to import and manage spatial datasets, perform spatial analysis, use packages like sf, raster, and terra, create maps and visualizations, and apply statistical models to spatial problems.
Basic knowledge of R is recommended, but the course is designed to guide beginners through the essentials of spatial data analysis. If you already have GIS experience, you’ll learn how to extend those skills with R’s scripting and automation power.
