Wallingford/ Lancaster (tbc)


from £399


Winter 2021

The feedback on the online course on 13-16 July 2021 was 97% positive.

"Ed and Phil were fantastic and really helpful, providing a great overview of spatial analysis in R and QGIS and providing many resources to pursue it further. Adding examples of code to analyse our own spatial data was a nice touch and will be particularly helpful." (Chris, PhD student, University of Sheffield, July 2021)

Please express your interest in future courses here so we can fix a new date.



Students £399 (later £449)     Professionals £449 (later £499)

(Early Bird discounts, then £50 more)


Short Course Description:

Running over four half-day sessions, this hands-on and interactive online course will give you an introduction to spatial data analysis in an open-source environment. The course will focus on the use of QGIS and R as well as providing a theoretical background to working with spatial data and Geographical Information Systems (GIS).

The course will help you to understand the key principals of working with spatial data in a Graphical User Interface (GUI) using QGIS and in a programming environment using R and show you how to perform the same tasks across both platforms.

You will learn best practices for processing spatial data and producing maps, allowing you to create high-quality outputs for environmental science. The course will have demonstrations alongside practical sessions, where you will learn by completing exercises, with skilled trainers on hand to guide and assist. Detailed documentation will also accompany the training, helping to walk you through the material and providing a useful resource for future learning.

Learning outcomes:

By the end of the course, you will be able to

  • Import, edit and export different types of spatial data in QGIS and R
  • Understand best practices in data processing
  • Work with base maps, plugins and visualisation tools to design effective maps
  • Process GIS datasets and understand the spatial relationship between them
  • Perform basic data analysis and validate datasets
  • Produce publication standard outputs

Course objectives:

  1. Gain awareness of different spatial data types commonly used across environmental science
  2. Identify and fix common errors/issues in data
  3. Learn the basics of good visualisation and best practice for cartography
  4. Become familiar with the QGIS interface, including useful plugins and extensions
  5. Learn how to use R (in the RStudio environment) as a GIS, including useful packages and visualisation tools.
  6. Explore the capabilities of QGIS and R for creating interactive and visually striking content.
  7. Feel confident in using open source software for spatial data analysis

Hardware/ Software requirements:

You will need a laptop or desktop computer. A second external screen will be an advantage (but is not essential).

We will use Zoom to deliver the training course. There are 5 ways to join Zoom (and at least one of them will work for you!). We will provide more information about Zoom with the joining instructions and at the start of the course. You can find more information about Zoom on our FAQ page.

We will do lots of practical exercises, so you can continue working on your skills immediately after the training course.  You will need to install this software before the course starts.

  • R programming language 4.0+ (free open source software)
  • R Studio Desktop (free open source software)
  • QGIS version 3.16+ (free open source software)

The course joining instructions will detail which specific software versions to download as well as guiding the installation process. It will be helpful if all participants use the same version for the course.


16 places


Beginner – Intermediate

Some knowledge of Geographical Information Systems and data analysis will be beneficial, but not essential. A basic understanding of the R programming language will be expected. UKCEH will provide links to introductory self-learning materials before the course.

Target Audience:

Anyone who is looking to work with spatial data in a reproducible manner and currently works mainly in spreadsheets or is looking to prepare spatial data for analysis in R.

Anyone who is looking to gain an understanding of spatial data in the environmental sector and wants to learn about free and open source software for GIS analysis.

e.g. MSc / PhD / Early Career Researchers, Ecologists & Environmental Scientists, Environmental Consultants etc.

Please express your interest in future courses here so we can fix a new date.

Course leaders:

Philip Taylor, Environmental Data Scientist, UKCEH

Philip is a data scientist and GIS expert who has worked with a large variety of environmental data for over 15 years, specialising in ecology, forestry, climate change and hydrology. An active member of the UK QGIS community, he helps with the QGIS Scotland chapter and was on the organising committee for FOSS4G UK 2019 (http://uk.osgeo.org/foss4guk2019/). He has run training courses in data handling, QGIS and R both nationally and internationally and is a member of the Centre of Excellence in Environmental Science (CEEDS).

Ed Carnell, Spatial Data Analyst, UKCEH 

Ed is a Spatial Data Analyst, specialising in the modelling of atmospheric emissions and their effect on human health and to sensitive habitats. His work includes producing high-resolution emission maps of air pollutants and greenhouse gases for the UK National Atmospheric Emission Inventory, as well as collaborating with international partners. He uses a code-based approach for data analysis and is a keen advocate of data transparency and quality assurance. He has taught training courses in QGIS, R and transforming environmental data.

Previous course participants said

"Phil and Ed were both really knowledgeable and helpful. They provided a lot of in depth content and were always happy to help when asked. I feel more familiar with the software and type of courses available. They were really good at adding content and letting us reach out to ask questions, which is really appreciated!" (a course participant, July 2021)

"I really liked that the same data was used throughout - it's easier to learn about the tools when the data is familiar rather than using new datasets for different parts of the course." (a course participant, July 2021)

"I really enjoyed it being on Zoom, it worked really well, Phil and Ed were engaging and answered everyone's questions really well. I learnt loads and it was a great experience, I would definitely recommend it." (a course participant, July 2021)