With R Routing, organizations can, for example, analyze the accessibility of facilities, calculate travel times, optimize cycling routes, or examine public transportation networks using OpenStreetMap data. In this blended learning course, you will learn how to perform route calculations, network analyses, and mobility analyses.
R Routing focuses on performing route calculations, accessibility analyses, and network analyses using the R programming language. Within Geo-ICT, this is important for issues related to mobility, infrastructure, public transportation, logistics, bicycle routes, and spatial accessibility.
With R, traffic networks, OpenStreetMap data, and public transportation data can be analyzed and combined with geographic datasets. Examples include calculating travel times, analyzing the accessibility of facilities, optimizing routes, or investigating mobility patterns. This creates a powerful environment for GIS, mobility analysis, and spatial data science.
What makes R so powerful is the combination of programmability, spatial analysis, and links to open data sources. This allows route and network calculations to be performed in a reproducible manner and easily repeated for different scenarios. Within Geo-ICT, R is increasingly being used for accessibility studies, mobility models, and policy analyses.
In this blended learning course, you will work with key routing packages such as osmdata, osrm, dodgr, stplanr, and tidytransit. You will learn to use OpenStreetMap data, calculate routes, analyze network distances, and process public transportation data.
In addition, R offers extensive capabilities for combining routing with visualization, statistics, databases, and spatial analysis. This makes this blended learning course particularly relevant for GIS specialists, mobility consultants, data analysts, policy staff, and Geo-ICT professionals who wish to conduct data-driven research on accessibility and mobility.
In this blended learning course, you will be introduced to the key capabilities of R for routing and mobility analysis. You will learn how to retrieve, process, and use OpenStreetMap data for route calculations and network analyses. You will work with packages such as osmdata, osrm, dodgr, stplanr, and tidytransit.
The course covers route calculation, network distances, travel time analyses, and accessibility issues. You’ll learn how to analyze routes for cars, bicycles, or pedestrians and how to translate results into actionable geographic insights.
You’ll also learn how R can be used for public transit data and mobility planning. With tidytransit, you’ll analyze stops, lines, schedules, and public transit accessibility. You’ll also discover how stplanr can be used for cycling, walking, and transit analyses.
During the blended learning course, you’ll work with practical datasets and learn how to set up reproducible routing workflows in R. Upon completion, you’ll be able to independently perform route calculations, accessibility analyses, and mobility analyses within GIS and Geo-ICT projects.
Do you already have experience with R Spatial Basics, R Databases, or R Visualization? Then this blended learning course is a logical next step toward mobility analysis, network data, and spatial accessibility within R.
Blended learning combines independent online learning with practical, interactive sessions, allowing you to understand both the basics of routing and the practical application of mobility analysis in R. In the online modules, you’ll learn how to use network data, calculate routes, and perform accessibility analyses with modern R packages.
You’ll discover how to work with OpenStreetMap data, routing engines, network distances, and public transit data. You’ll also learn how to combine routing results with visualization, spatial analysis, and reporting within R. 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 execute routing workflows using packages such as osmdata, osrm, dodgr, stplanr, and tidytransit.
The combination of online learning and interactive hands-on experience ensures that you not only learn how routes are calculated technically, but also how to analyze accessibility and mobility in depth. After completing the blended learning program, you will be able to professionally apply routing and mobility analyses within Geo-ICT, GIS, and spatial policy projects.
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 knowledge of R and GIS is helpful, but experience with routing or mobility analysis is not required. During the blended learning course, route calculations and network analyses are explained step by step using practical Geo-ICT examples.
During the blended learning program, you will work with route calculations, travel time analyses, accessibility analyses, network distances, mobility patterns, and public transportation analyses based on geographic network data.
Yes. OpenStreetMap is an important data source in this blended learning course. You will learn how to retrieve road, bicycle, walking, and network data and use it for routing and mobility analysis in R.
Yes. Routing results and network data can be easily combined with GIS software such as QGIS and, to a lesser extent, ArcGIS for further analysis, visualization, and map production within Geo-ICT workflows.
During the blended learning program, you will work with tools such as osmdata, osrm, dodgr, stplanr, and tidytransit for route calculation, OpenStreetMap data, network analysis, and public transportation data within R.
