Introduction to R for Spatial Data Analysis
26 January 2016
R is one of the fastest growing languages for data analysis and is increasingly important in business, government and academia. Less well-known is that R has a diverse suite of geospatial tools and can function as a fully integrated Geographical Information System (GIS). Time-series maps, geographically weighted regression, animations and even online maps become possible when you understand R’s unique language and approach to spatial objects.
However, as with any language, it is important to gain a strong understanding of the underlying syntax and structure before moving on to complex uses. This course therefore focuses on the foundations: how R can be used to load, manipulate, process, transform and visualise spatial data. Prior experience with R is not essential but is recommended; participants will also benefit from experience with GIS.
By the end of the course participants will:
- Understand the structure of spatial data in R
- Be able to query, subset and analyse spatial objects
- Have a working knowledge of fundamental GIS functions such as changing projections
- Be proficient in the use of R to create maps using add-on packages such as tmap
For more information on the course, please see here.
Who teaches the programme?
Dr Robin Lovelace is a quantitative geographer and environmental scientist working as Research Fellow at the Consumer Data Research Centre (CDRC) at the University of Leeds, UK. Robin developed the popular tutorial Introduction to Spatial Data with R.
Is this course for me?
Working knowledge of R and RStudio is assumed. We are offering an introduction to R and RStudio on the 25th January – please see details here.
Background reading “A (very) short introduction to R”, Paul Torfs & Claudia Brauer
Leeds Institute for Data Analytics
University of Leeds