Learn R for Spatial Analysis

External resources and tutorials

R for Geospatial Analysis

While our primary focus is QGIS, R is another powerful tool for spatial data analysis and visualization. Below are curated external resources to help you learn R for geospatial work.

Recommended Courses

Rbanism Geospatial Data Carpentry

A comprehensive introduction to working with geospatial data in R, focused on urban applications.

Topics covered: - Introduction to R and RStudio - Working with vector data (sf package) - Working with raster data (terra package) - Spatial operations and analysis - Creating maps with ggplot2

Visit Course →

Community Challenges

#30DayMapChallenge

Join the annual mapping challenge! Create 30 maps in 30 days using R and share with the community.

What you’ll learn: - Daily mapping practice - Data visualization techniques - Creative problem-solving - Community engagement

Learn More →

Rbanism Challenge Resources →

Additional Resources

Books & Documentation

Geocomputation with R - Comprehensive guide to spatial analysis
Spatial Data Science - Advanced spatial data methods
R for Data Science - General R programming foundation

Key R Packages

sf: Simple features for vector data
terra: Spatial data analysis for raster data
tmap: Thematic map creation
leaflet: Interactive web maps
ggplot2: Data visualization

Why Learn Both QGIS and R?

QGIS and R complement each other well:

QGIS	R
Visual, interactive interface	Code-based, reproducible
Quick exploration	Automated workflows
Print-ready maps	Statistical analysis
Beginner-friendly	Powerful scripting

Pro tip: Use QGIS for exploration and map design, then use R for reproducible analysis and batch processing.

Questions?

Need help getting started with R? Check our Contact page or join our community discussions.