Geocomputation and Data Analysis with R

Description:

Run in conjunction with Leeds Digital Festival 2020, this two-day course aims to get you up-to-speed with high performance geographic processing, analysis and visualisation capabilities from the command-line. The course will be delivered in R, a statistical programming language popular in academia, industry and, increasingly, the public sector. It will teach a range of techniques using recent developments in the package sf and the ‘metapackage’ tidyverse, based on the open source book Geocomputation with R (Lovelace, Nowosad, and Meunchow 2019).

Learning Objectives

By the end of the course participants should:

• Be able to use R and RStudio as a powerful Geographic Information System (GIS)
• Know how R’s spatial capabilities fit within the landscape of open source GIS software
• Be confident with using R’s command-line interface (CLI) and scripting capabilities for geographic data processing
• Understand how to import a range of data sources into R
• Be able to perform a range of attribute operations such as subsetting and joining
• Understand how to implement a range of spatial data operations including spatial subsetting and spatial aggregation
• Have the confidence to output the results of geographic research in the form of static and interactive maps.

Course Tutor

Robin Lovelace is a researcher at the Leeds Institute for Transport Studies (ITS) and the Leeds Institute for Data Analytics (LIDA). Robin has over a decade of experience using R for academic research and has taught numerous R courses at all levels. He has developed popular R resources including the book Efficient R Programming (Gillespie and Lovelace 2016), Introduction to Visualising Spatial Data in R  and Spatial Microsimulation with R (Lovelace and Dumont 2016). These skills have been applied on a number of projects with real-world applications, including the Propensity to Cycle Tool (PCT) a nationally scalable interactive online mapping application, and the stplanr package.

Is this course for me?

This is not an introductory R course but a course for R users wanting to develop their geospatial analysis skills, and as such attendees should already have experience with R. In addition to being able to complete introductory courses such as DataCamp’s introduction to R or equivalent, attendees should already be using R for their work.  If you do not have R experience but already use GIS software and have a strong understanding for geographic data types, and some programming experience, the course may also be appropriate. Attendees are expected to bring their own laptops and will be emailed a list of packages to install.

In preparation for the course we recommend reading and running the code in these free online resources:

• The introductory chapter of R for Data Science
• Chapter 2 on setting-up R and section 4.4 on package selection in the book Efficient R Programming

Cost:

The course is open to students, academic staff and external delegates.

Early Bird rate (until 22nd March 2020)

£200 – Students

£400 – Academics, charitable and public sector

£700 – Other

Rates 23rd March-21st April 2020

£300 – Students

£500 – Academics, charitable and public sector

£800 – Other

The fee includes learning materials, lunch and refreshments during the course, but not overnight accommodation.

Website and registration:

https://store.leeds.ac.uk/conferences-and-events/environment/geography/0420gdar2-geocomputation-and-data-analysis-with-r

Region:

Yorkshire and Humberside

Keywords:

Quantitative Data Handling and Data Analysis, ICT and Software, R , Geospatial , Maps , tidyverse , visualisation

Related publications and presentations:

Quantitative Data Handling and Data Analysis
ICT and Software

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