Geographical Data Science and Spatial Data Analysis
A Comprehensive Guide to Analyzing Spatial Data with R
Created by Chris Brunsdon, Lex Comber
Explore the world of geographical data science by working directly with spatial data in R. You'll move from data wrangling and visualization to advanced analysis and machine learning. Practical examples and real-world projects help you build confidence as you solve spatial data challenges.
Sage Publishing | Jul 2026 | 360 min
What You Will Learn
You will gain hands-on experience by working through practical examples that use real spatial datasets. Starting with foundational data wrangling and visualization, you'll progress to more advanced topics like spatial databases and machine learning. Each step builds your skills and prepares you to tackle real-world spatial analysis tasks.
Key Features
- Manipulate and visualize spatial data using R and tidyverse tools
- Apply machine learning to uncover patterns in spatial datasets
- Query and analyze spatial databases for deeper geographical insights
Target Audience
Designed for those with a solid grasp of R and tidyverse basics, this content is ideal if you want to expand your skills into geographical data science. It's especially useful for professionals in environmental science, urban planning, or geospatial analytics who want to apply data science techniques to spatial problems.
