Spatial Data Analysis & Visualisation in R
As spatial data sets grow ever larger this course will teach you how to harness the capabilities of R for your analysis.
Description
As spatial data sets grow ever larger, better 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.
2023 Prior knowledge
It is expected that participants will have basic R experience, e.g. attending an Introduction to R course or having a similar level of knowledge. A good benchmark would be being comfortable with the first 5 chapters of the freely available R for Data Science book. We’re happy to respond to individual queries about prior experience required and can provide more guidance if required.
2023 Online Platform and Software Requirements
Computer with video camera, speakers and microphone
Stable internet connection
Mains power
Zoom
Virtual Classroom - Tutor will send direct the link to the virtual classroom
The tutor provides a bespoke virtual training environment.
2023 Topics
Introduction to {sf}, a package for handling data.
Explore the difference between handling traditional data and spatial data in R.
Learn to create static and interactive web-based maps.
Key concepts such as spatial joins and coordinate reference systems.
2023 Course goals and outcomes
How R can be used as a tool for GIS (Geographic Information System) mapping
How to load and interrogate spatial objects in R with the {sf} package
Visualising maps with the {tmap} package
Spatial data manipulation including joining spatial data
Creating interactive maps with the leaflet package.
2023 Audience
Those who wishes to use R to create interactive maps from their data sets.