Spatial Data Analysis in R - Virtual Classroom

Date: Thursday 19 May 2022, 1.00PM
Location: Online
CPD: 6.0 hours
RSS Training


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Level: Intermediate (I)


This virtual course will run over 2 afternoons. As spatial datasets get larger and 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. 

Please note: Bookings will close 4 working days before the course start date or when the course has reached its maximum capacity.
 
Level: Intermediate (I)


As spatial datasets get larger and 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. 

This training course provides an introduction to sf, a popular package for handling geographic data in R. Participants will learn how to load, manipulate and visualise geographic vector data, creating both static and interactive maps. The focus is on the principles rather than the specific methods, providing participants with the understanding needed to apply R's powerful suite of geographical tools to their own problems.
 

Topics Covered

  • Introducing R as a GIS
  • The structure of spatial objects in R
  • Loading and interrogating spatial data
  • Visualisaing spatial datasets with tmap
  • Data manipulation with spatial data using dplyr
  • Spatial operations such as intersections
  • Interactive maps with leaflet
 

Target Audience

Participants with spatial data problems who are not making use of R and are falling behind in the ever changing world of data science.
 

Assumed Knowledge

A basic understanding of the R software is assumed. 

Each participant will to install with the latest versions of Rstudio and R software.

 

Dr. Nicola Rennie

Nicola has a PhD in Statistics and Operational Research, with a focus on outlier detection in functional data. She enjoys sharing her knowledge of R, creating data visualisations, working closely with clients to help them get the most from their data.

 

Fees

   

Registration before
 19 April 2022

 

Registration on/after
 19 April 2022

                                  


Non Member 

RSS Fellow 

RSS CStat/Gradstat/Data Analyst 
also MIS & FIS

 

£399.84+vat 

£338.64+vat 

£320.28+vat

£443.70+vat 

£377.40vat 

£355.98+vat