The feedback for the interactive online course in March 2024 was 98% positive.
Location:
Interactive online course delivered via Zoom (more details below)
Cost:
Students: £499
Professionals: £549
Dates:
18-22 November 2024 Sold Out!
The next course will run in early 2025.
Please express your interest here, so we can fix more course dates in 2025!
Course structure:
Monday 18 November: (Day 1) 2-3 pm software familiarisation drop-in session (optional)
Main course Tue 19 Nov- Fri 22 Nov 9:30 - 1 pm
Afternoon learning is optional. You will benefit most from the course if you have some time for recap and self-taught learning.
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). This is a beginner's course for spatial analysis. Having basic knowledge of (non-spatial) R is strongly recommended.
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 similar 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 allows you to learn by doing practical sessions alongside the trainer. The trainers are always on hand to guide and assist. Detailed documentation will also accompany the training, helping you to walk through the material and provide 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:
- Gain awareness of different spatial data types commonly used across environmental science
- Identify and fix common errors/issues in data
- Learn the basics of good visualisation and best practice for cartography
- Become familiar with the QGIS interface, including useful plugins and extensions
- Learn how to use R (in the RStudio environment) as a GIS, including useful packages and visualisation tools.
- Explore the capabilities of QGIS and R for creating interactive and visually striking content.
- Feel confident in using open-source software for spatial data analysis
Target audience:
Anyone who is looking to work with spatial data in a reproducible manner in an open source environment.
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.
Level:
Beginner
A basic understanding of the R programming language will be expected. UKCEH will provide links to introductory self-learning materials before the course. If you are a beginner to R, it is essential that you do some learning on R before the course starts.
Places:
18 places
Hardware/ software requirements:
You will need a laptop or desktop computer. We highly recommend you use a second monitor, as you will need to perform actions alongside the demonstrations.
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 recommend that you install the Zoom program if you are able to do so: https://ukceh-ac-uk.zoom.us/test
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 4.4+ (free open-source software)
- R Studio Desktop (free open-source software)
- QGIS version 3.28+ (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.
Having a webcam is desirable (but not essential). If you plan to participate from an open-plan office or noisy environment, please wear headphones with a built-in microphone.
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.
Erica Zaja, Environmental Data Scientist, UKCEH
Erica is an environmental data scientist, with an ecology and environmental management background. Erica is experienced in managing and analysing large datasets to drive impactful environmental insights.
Clare Pearson, Spatial Data Analyst, UKCEH
Rachel Nickerson, Inventory Data Analyst, UKCEH
Previous course participants said:
The feedback for the interactive online course in March 2024 was 98% positive.
''I particularly liked that you could follow along. The move from the basics into advanced was really well done.'' (Rachel Nichols, Goodwill Charitable Trust, July 2024)
''Really useful training. I like how interactive the course was. It was a great course. I have benefitted a lot from it and feel very confident about the proceeding with my work.'' (Chisha Mzyece, Stirling University, July 2024)
''The course was very helpful in re-affirming the basic concepts while also introducing new methods of analysis and visualisation. The course teachers were very knowledgeable and helpful, offering clear and concise instructions'' (Christian Gossel, Organic Research Centre, March 2024)
''Excellent course delivered at an appropriate pace with great examples used throughout. Would recommend to anyone starting out in using spatial data'' (Learner, March 2024)
''Brilliant. I enjoyed it thoroughly. Very well run and well-organised; the trainers were so knowledgeable and always approachable. Very impressed, especially for a virtual course. The breadth of topics covered was really good. Thank you!'' (Lucy Baldwin, North & East Yorkshire ecological data centre, December 2023)
''This is an excellent course with a good pace, which allowed all participants to be included. Trainers were excellent and very knowledgeable.'' (Matthew Morgan, Hull University, December 2023)
“Excellent course, really useful in so many contexts, thank you very much!” (James Kershaw, Bristol University, January 2023)
“I found the course very informative and engaging, the pace of the course was just right, giving us time to follow along and keep up but still covering a lot of ground. Both the trainers were engaging and helpful, being quick to respond to feedback and answer questions.” (Samuel Aizlewood, Kent University, January 2023)