With R, organizations can develop interactive web maps, 3D terrain visualizations, dashboards, and cartographic analyses for applications such as mobility, infrastructure, ecology, and smart cities. In this blended learning course on R Visualization, you will learn how to professionally visualize geographic data using modern R packages for interactive maps, data storytelling, and spatial dashboards.
R Visualization focuses on creating clear, interactive, and professional visualizations using the R programming language. Within Geo-ICT, this involves not only graphs, but primarily maps, dashboards, 3D visualizations, and visual analyses of geographic data.
With R, geographic datasets can be converted into understandable maps and interactive applications. Examples include web maps for policy information, dashboards for monitoring, 3D terrain visualizations, thematic maps, and visual analyses of spatial patterns. This creates a powerful environment for data storytelling within GIS, spatial data science, and Geo-ICT.
What makes R so powerful is the combination of cartography, statistics, programmability, and interactive visualization. This allows maps and graphs to be constructed in a reproducible manner and easily adapted to different audiences. Within Geo-ICT, R is increasingly used not only to perform spatial analyses but also to present them clearly and persuasively.
In this blended learning course, you will work with key visualization packages such as leaflet, mapview, tmap, ggplot2, ggspatial, cartography, plotly, rayshader, mapdeck, and leaflet.extras. You will learn to create interactive maps, thematic map visualizations, graphs, 3D visualizations, and web-oriented geo-visualizations.
In addition, R offers extensive capabilities for combining visualizations with analysis, reporting, and automation. This makes this blended learning course particularly relevant for GIS specialists, data analysts, researchers, policy analysts, and Geo-ICT professionals who wish to clearly present and share geographic data.
In this blended learning course, you will be introduced to the key capabilities of R for geo-visualization. You will learn how to convert geographic datasets into clear maps, interactive web maps, and visual analyses. You will work with packages such as leaflet, tmap, ggplot2, mapview, and plotly.
Attention is given to cartographic principles, thematic maps, interactive map layers, pop-ups, legends, scale bars, and map layout. You will learn how to present spatial data in a visually appealing and factually accurate manner for various applications within Geo-ICT.
In addition, you will learn how R can be used for more advanced forms of visualization. Using packages such as rayshader and mapdeck, you will work on 3D visualizations, terrain images, and interactive map displays. You will also discover how leaflet.extras adds extra functionality to interactive web maps.
During the blended learning program, you’ll work with practical datasets and learn how to set up reproducible visualizations in R. Upon completion, you’ll be able to independently create maps, graphs, and interactive geo-visualizations for reports, dashboards, analyses, and online applications.
Do you already have experience with R Spatial Basics or R Data Science? Then this blended learning course is a logical next step to professionally visualize analysis results and make them more accessible to clients, colleagues, and end users.
Blended learning combines independent online learning with practical, interactive sessions, allowing you to understand both the cartographic fundamentals and the practical application of geo-visualization in R. In the online modules, you’ll learn how to convert geographic data into maps, graphs, and interactive visualizations using modern R packages.
You’ll discover how to create thematic maps, build interactive web maps, and present spatial information clearly. You’ll also learn how 2D and 3D visualizations can help make complex geographic patterns easier to understand. Thanks to unlimited access to the course materials, you can review and practice the material at your own pace.
During the hands-on online sessions, you’ll immediately apply the theory to realistic datasets and familiar Geo-ICT challenges. You’ll receive guidance from experienced instructors and learn how to create visualizations using packages such as Leaflet, tmap, ggplot2, Plotly, Rayshader, and Mapdeck.
The combination of online learning and interactive hands-on experience ensures that you not only learn how to create maps and graphs, but also how to communicate spatial information effectively. After completing the blended learning program, you will be able to professionally visualize geographic data and make valuable insights accessible to various audiences.
You’ll receive 1-on-1 guidance. After signing up, our course coordinator will contact you to schedule your first session.
Do you have questions about the course content? Or are you unsure whether the course aligns with your learning goals or preferences? Would you prefer an in-house or private course? We’d be happy to help.
A basic understanding of R is helpful, but extensive programming experience is not required. During the blended learning course, visualizations are built step by step using practical examples and geographic datasets.
Traditional GIS software often focuses on manual map production, whereas R makes visualizations reproducible and automatable. This allows interactive maps, dashboards, and dynamic visualizations to be developed and replicated more efficiently.
During the blended learning course, you will learn how to create interactive web maps, thematic maps, dashboards, charts, 2D and 3D terrain visualizations, and dynamic geo-visualizations using various R packages.
Yes. R is often used in conjunction with GIS software such as QGIS and, to a lesser extent, ArcGIS. Geographic datasets can be easily exchanged, after which R can be used for advanced visualizations, dashboards, and interactive maps.
During the blended learning program, you will work with tools such as Leaflet, MapView, TMap, ggplot2, ggspatial, cartography, Plotly, RayShader, MapDeck, and Leaflet.extras to create interactive maps, cartography, and 3D visualizations.
