Introduction to QGis
Date: 26 February 2020
Instructor: Samuel Langton
CMI offers up to five subsidised places at a reduced rate of £60 per course day to research staff and students within Humanities at The University of Manchester. These places are awarded in order of application.
Humanities PGR students at The University of Manchester can apply for a methods@manchester bursary to help cover their costs. All applications will be considered on a case-by-case basis and applicants will be required to provide a supporting statement from their supervisor.
Please click here to make a booking. If you are applying for a subsidised place, select the £60 University of Manchester option on the booking form. For queries about methods@manchester bursaries, contact email@example.com (please note, you must have a confirmed place on the course before requesting a bursary application form). For any other queries about short courses, please contact firstname.lastname@example.org.
Please note: this is not guaranteed and is considered on a case by case basis. Please contact us for more information.
Part of Social Data Science Week, a collaboration between the Cathie Marsh Institute and methods@manchester. These courses have been designed for postgraduate researchers, giving you the tools to make use of free and open-source software, and techniques from the cutting-edge new discipline of social data science.
This course will introduce attendees to QGIS, an open piece of software used for handling, visualising, exploring and analysing geographic information.
The goals of this one day workshop are:
Introduce QGIS as a powerful (and free) GIS tool.
How to load in data and perform preliminary visual explorations.
How to handle and manipulate spatial data.
How to create aesthetically beautiful (but accurate and useful) maps according to fundamental data visualisation principles.
How to engage critically with maps and your own data.
There will be an opportunity for attendees to use their own data during the day.
Attendees will engage with fundamental principles common to all GIS research but also learn applied skills within QGIS, including how to load, handle, manipulate, visualise and explore spatial data.
No prior knowledge of GIS or QGIS is required.
About the instructor
Sam Langton is a research associate at the Manchester Metropolitan Crime and Well-being Big Data Centre. His doctoral research focused on the geographic distribution of crime and known offender residences in Birmingham, particularly in terms of longitudinal stability and the impact of spatial scale. Sam is currently working on projects in collaboration with Greater Manchester Police. He has conducted a number of training courses on open software for postgraduate students and academic staff at the University of Manchester, as well as police force personnel.