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CPD - R for Spatial Analysis

CDRC Training
Friday 6 October 2017, 9am - 4:30pm
Leeds Institute for Data Analytics, Level 11, Worsley Building, University of Leeds, Clarendon Way, Leeds, LS2 9NL

This one day course will get you up-to-speed with using R and RStudio for daily working with spatial data. You will learn about R’s powerful geospatial data processing, analysis and visualisation capabilities. It is practical and hands-on: you’ll learn by doing. It assumes you already use R and want to extend your knowledge for spatial data applications. It will cover the recently developed sf package, which is compatible with the tidyverse, representing the cutting-edge of spatial data applications. It will provide a solid foundation (including spatial aggregation, joining, CRSs, visualisation) on which advanced analysis analysis workflows can be built.

Learning outcomes

By the end of the course participants will:

  • Understand R’s spatial ecosystem and which packages are ‘future proof’
  • Know how to optimise RStudio for productive working with spatial data (you should already be proficient with RStudio)
  • Be able to read and write a variety of spatial data formats
  • Be proficient at common spatial operations including subsetting, cropping, aggregation and transformation
  • Be a confident map maker using the powerful tmap package
  • Know where to look for learning more advanced methods

Course materials

The course will be based on the first 5 chapters of the forethcoming book Geocomputation with R plus some additional materials:

  • An introduction to geographic data in R
  • Spatial data operations
  • Geographic data I/O
  • Introduction to visualising spatial data with R
  • Point pattern analysis and rasterization

Course agenda 

Refreshments & set-up: (09:00 – 09:30)

  • R’s spatial ecosystem: (09:30 – 10:00)
  • R and RStudio for spatial data (10:00 – 10:30)
  • An interactive spatial data workflow: (10:00 – 10:45)

Coffee break: (10:45 – 11:00)

  • Geographic data in R: simple features (11:00 – 12:00)
  • Raster data classes and functions (12:00 – 12:30)

LUNCH and looking at your data (12:30 – 13:30)

  • Spatial data operations (13:30 – 14:30)
  • Visualisation (14:30 – 15:00)

Coffee break: 15:00 – 15:15

  • Geographic data I/O: (15:15 – 15:45)
  • Point pattern analysis, interpolation and rasterization: (15:45 – 16:00)
  • Working with your data and next steps (16:00 – 16:30)


Dr Robin Lovelace