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Training Course Details

Spatial Data Analysis with R

Spatial Data Analysis with R

Course Level: Advanced

As spatial data sets get larger, more sophisticated software needs to be harnessed for their analysis. R is now a widely used open source software platform for working with spatial data thanks to its powerful analysis and visualisation packages. The focus of this course is providing participants with the understanding needed to apply R’s powerful suite of geographical tools to their own problems.

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Course Details

  • Course Outline
  • Learning Outcomes
  • Materials
  • Prior Knowledge

Course Outline

This course will be structured as follows:

  • Introducing R as a GIS
  • The structure of spatial objects in R
  • Loading and interrogating spatial data with {sf}
  • Visualising spatial data sets with {tmap}
  • Data manipulation with spatial data using {dplyr}
  • Spatial joins
  • Coordinate reference systems (CRS)
  • Interactive maps with {leaflet}

Learning Outcomes

By the end of the day participants will…

  • have learned how spatial data is stored and how to import such data into R
  • be able to visualise data in the form of static maps
  • understand how to manipulate spatial data using {dplyr} functionality
  • develop an understanding as to the importance of CRS in describing geographic data
  • be able to create interactive maps to visualise their data

Materials

  • Page 1 of example course material for Spatial Data Analysis with R
  • Page 2 of example course material for Spatial Data Analysis with R
  • Page 3 of example course material for Spatial Data Analysis with R
  • Page 4 of example course material for Spatial Data Analysis with R
  • Page 5 of example course material for Spatial Data Analysis with R

Prior Knowledge

It is expected that participants have basic R experience, e.g. attending the Introduction to R and Programming with R courses or having a similar level of knowledge. The course will be hands-on and applied with short introductory lectures to each of the topics, followed by practical sessions loading and analysing real spatial datasets.

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